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approximation method</title> <meta name="description" content="Search results for: Vogel’s approximation method"> <meta name="keywords" content="Vogel’s approximation method"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button 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action="https://publications.waset.org/abstracts/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="Vogel’s approximation method"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 19207</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: Vogel’s approximation method</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19207</span> Modified Approximation Methods for Finding an Optimal Solution for the Transportation Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=N.%20Guruprasad">N. Guruprasad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents a modification of approximation method for transportation problems. The initial basic feasible solution can be computed using either Russel's or Vogel's approximation methods. Russell’s approximation method provides another excellent criterion that is still quick to implement on a computer (not manually) In most cases Russel's method yields a better initial solution, though it takes longer than Vogel's method (finding the next entering variable in Russel's method is in O(n1*n2), and in O(n1+n2) for Vogel's method). However, Russel's method normally has a lesser total running time because less pivots are required to reach the optimum for all but small problem sizes (n1+n2=~20). With this motivation behind we have incorporated a variation of the same – what we have proposed it has TMC (Total Modified Cost) to obtain fast and efficient solutions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=computation" title="computation">computation</a>, <a href="https://publications.waset.org/abstracts/search?q=efficiency" title=" efficiency"> efficiency</a>, <a href="https://publications.waset.org/abstracts/search?q=modified%20cost" title=" modified cost"> modified cost</a>, <a href="https://publications.waset.org/abstracts/search?q=Russell%E2%80%99s%20approximation%20method" title=" Russell’s approximation method"> Russell’s approximation method</a>, <a href="https://publications.waset.org/abstracts/search?q=transportation" title=" transportation"> transportation</a>, <a href="https://publications.waset.org/abstracts/search?q=Vogel%E2%80%99s%20approximation%20method" title=" Vogel’s approximation method"> Vogel’s approximation method</a> </p> <a href="https://publications.waset.org/abstracts/19162/modified-approximation-methods-for-finding-an-optimal-solution-for-the-transportation-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/19162.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">547</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19206</span> Solving the Transportation Problem for Warehouses and Dealers in Bangalore City</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=S.%20Aditya">S. Aditya</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20T.%20Nideesh"> K. T. Nideesh</a>, <a href="https://publications.waset.org/abstracts/search?q=N.%20Guruprasad"> N. Guruprasad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Being a subclass of linear programing problem, the Transportation Problem is a classic Operations Research problem where the objective is to determine the schedule for transporting goods from source to destination in a way that minimizes the shipping cost while satisfying supply and demand constraints. In this paper, we are representing the transportation problem for various warehouses along with various dealers situated in Bangalore city to reduce the transportation cost incurred by them as of now. The problem is solved by obtaining the Initial Basic feasible Solution through various methods and further proceeding to obtain optimal cost. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=NW%20method" title="NW method">NW method</a>, <a href="https://publications.waset.org/abstracts/search?q=optimum%20utilization" title=" optimum utilization"> optimum utilization</a>, <a href="https://publications.waset.org/abstracts/search?q=transportation%20problem" title=" transportation problem"> transportation problem</a>, <a href="https://publications.waset.org/abstracts/search?q=Vogel%E2%80%99s%20approximation%20method" title=" Vogel’s approximation method"> Vogel’s approximation method</a> </p> <a href="https://publications.waset.org/abstracts/19160/solving-the-transportation-problem-for-warehouses-and-dealers-in-bangalore-city" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/19160.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">437</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19205</span> Solutions of Fuzzy Transportation Problem Using Best Candidates Method and Different Ranking Techniques</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20S.%20Annie%20Christi">M. S. Annie Christi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Transportation Problem (TP) is based on supply and demand of commodities transported from one source to the different destinations. Usual methods for finding solution of TPs are North-West Corner Rule, Least Cost Method Vogel’s Approximation Method etc. The transportation costs tend to vary at each time. We can use fuzzy numbers which would give solution according to this situation. In this study the Best Candidate Method (BCM) is applied. For ranking Centroid Ranking Technique (CRT) and Robust Ranking Technique have been adopted to transform the fuzzy TP and the above methods are applied to EDWARDS Vacuum Company, Crawley, in West Sussex in the United Kingdom. A Comparative study is also given<strong>.</strong> We see that the transportation cost can be minimized by the application of CRT under BCM. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=best%20candidate%20method" title="best candidate method">best candidate method</a>, <a href="https://publications.waset.org/abstracts/search?q=centroid%20ranking%20technique" title=" centroid ranking technique"> centroid ranking technique</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20transportation%20problem" title=" fuzzy transportation problem"> fuzzy transportation problem</a>, <a href="https://publications.waset.org/abstracts/search?q=robust%20ranking%20technique" title=" robust ranking technique"> robust ranking technique</a>, <a href="https://publications.waset.org/abstracts/search?q=transportation%20problem" title=" transportation problem"> transportation problem</a> </p> <a href="https://publications.waset.org/abstracts/60506/solutions-of-fuzzy-transportation-problem-using-best-candidates-method-and-different-ranking-techniques" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/60506.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">294</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19204</span> Approximation Property Pass to Free Product</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kankeyanathan%20Kannan">Kankeyanathan Kannan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> On approximation properties of group C* algebras is everywhere; it is powerful, important, backbone of countless breakthroughs. For a discrete group G, let A(G) denote its Fourier algebra, and let M₀A(G) denote the space of completely bounded Fourier multipliers on G. An approximate identity on G is a sequence (Φn) of finitely supported functions such that (Φn) uniformly converge to constant function 1 In this paper we prove that approximation property pass to free product. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=approximation%20property" title="approximation property">approximation property</a>, <a href="https://publications.waset.org/abstracts/search?q=weakly%20amenable" title=" weakly amenable"> weakly amenable</a>, <a href="https://publications.waset.org/abstracts/search?q=strong%20invariant%20approximation%20property" title=" strong invariant approximation property"> strong invariant approximation property</a>, <a href="https://publications.waset.org/abstracts/search?q=invariant%20approximation%20property" title=" invariant approximation property"> invariant approximation property</a> </p> <a href="https://publications.waset.org/abstracts/44414/approximation-property-pass-to-free-product" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/44414.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">675</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19203</span> Improved Pitch Detection Using Fourier Approximation Method</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Balachandra%20Kumaraswamy">Balachandra Kumaraswamy</a>, <a href="https://publications.waset.org/abstracts/search?q=P.%20G.%20Poonacha"> P. G. Poonacha</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Automatic Music Information Retrieval has been one of the challenging topics of research for a few decades now with several interesting approaches reported in the literature. In this paper we have developed a pitch extraction method based on a finite Fourier series approximation to the given window of samples. We then estimate pitch as the fundamental period of the finite Fourier series approximation to the given window of samples. This method uses analysis of the strength of harmonics present in the signal to reduce octave as well as harmonic errors. The performance of our method is compared with three best known methods for pitch extraction, namely, Yin, Windowed Special Normalization of the Auto-Correlation Function and Harmonic Product Spectrum methods of pitch extraction. Our study with artificially created signals as well as music files show that Fourier Approximation method gives much better estimate of pitch with less octave and harmonic errors. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=pitch" title="pitch">pitch</a>, <a href="https://publications.waset.org/abstracts/search?q=fourier%20series" title=" fourier series"> fourier series</a>, <a href="https://publications.waset.org/abstracts/search?q=yin" title=" yin"> yin</a>, <a href="https://publications.waset.org/abstracts/search?q=normalization%20of%20the%20auto-%20correlation%20function" title=" normalization of the auto- correlation function"> normalization of the auto- correlation function</a>, <a href="https://publications.waset.org/abstracts/search?q=harmonic%20product" title=" harmonic product"> harmonic product</a>, <a href="https://publications.waset.org/abstracts/search?q=mean%20square%20error" title=" mean square error"> mean square error</a> </p> <a href="https://publications.waset.org/abstracts/36472/improved-pitch-detection-using-fourier-approximation-method" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/36472.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">412</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19202</span> Approximation of the Time Series by Fractal Brownian Motion</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Valeria%20Bondarenko">Valeria Bondarenko</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we propose two problems related to fractal Brownian motion. First problem is simultaneous estimation of two parameters, Hurst exponent and the volatility, that describe this random process. Numerical tests for the simulated fBm provided an efficient method. Second problem is approximation of the increments of the observed time series by a power function by increments from the fractional Brownian motion. Approximation and estimation are shown on the example of real data, daily deposit interest rates. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fractional%20Brownian%20motion" title="fractional Brownian motion">fractional Brownian motion</a>, <a href="https://publications.waset.org/abstracts/search?q=Gausssian%20processes" title=" Gausssian processes"> Gausssian processes</a>, <a href="https://publications.waset.org/abstracts/search?q=approximation" title=" approximation"> approximation</a>, <a href="https://publications.waset.org/abstracts/search?q=time%20series" title=" time series"> time series</a>, <a href="https://publications.waset.org/abstracts/search?q=estimation%20of%20properties%20of%20the%20model" title=" estimation of properties of the model"> estimation of properties of the model</a> </p> <a href="https://publications.waset.org/abstracts/4285/approximation-of-the-time-series-by-fractal-brownian-motion" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/4285.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">376</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19201</span> High-Pressure Calculations of the Elastic Properties of ZnSx Se 1−x Alloy in the Virtual-Crystal Approximation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=N.%20Lebga">N. Lebga</a>, <a href="https://publications.waset.org/abstracts/search?q=Kh.%20Bouamama"> Kh. Bouamama</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20Kassali"> K. Kassali</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We report first-principles calculation results on the structural and elastic properties of ZnS x Se1−x alloy for which we employed the virtual crystal approximation provided with the ABINIT program. The calculations done using density functional theory within the local density approximation and employing the virtual-crystal approximation, we made a comparative study between the numerical results obtained from ab-initio calculation using ABINIT or Wien2k within the Density Functional Theory framework with either Local Density Approximation or Generalized Gradient approximation and the pseudo-potential plane-wave method with the Hartwigzen Goedecker Hutter scheme potentials. It is found that the lattice parameter, the phase transition pressure, and the elastic constants (and their derivative with respect to the pressure) follow a quadratic law in x. The variation of the elastic constants is also numerically studied and the phase transformations are discussed in relation to the mechanical stability criteria. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=density%20functional%20theory" title="density functional theory">density functional theory</a>, <a href="https://publications.waset.org/abstracts/search?q=elastic%20properties" title=" elastic properties"> elastic properties</a>, <a href="https://publications.waset.org/abstracts/search?q=ZnS" title=" ZnS"> ZnS</a>, <a href="https://publications.waset.org/abstracts/search?q=ZnSe" title=" ZnSe"> ZnSe</a>, <a href="https://publications.waset.org/abstracts/search?q=" title=" "> </a> </p> <a href="https://publications.waset.org/abstracts/33371/high-pressure-calculations-of-the-elastic-properties-of-znsx-se-1x-alloy-in-the-virtual-crystal-approximation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/33371.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">574</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19200</span> Degree of Approximation of Functions by Product Means</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hare%20Krishna%20Nigam">Hare Krishna Nigam</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, for the first time, (E,q)(C,2) product summability method is introduced and two quite new results on degree of approximation of the function f belonging to Lip (alpha,r)class and W(L(r), xi(t)) class by (E,q)(C,2) product means of Fourier series, has been obtained. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Degree%20of%20approximation" title="Degree of approximation">Degree of approximation</a>, <a href="https://publications.waset.org/abstracts/search?q=%28E" title=" (E"> (E</a>, <a href="https://publications.waset.org/abstracts/search?q=q%29%28C" title="q)(C">q)(C</a>, <a href="https://publications.waset.org/abstracts/search?q=2%29%20means" title="2) means">2) means</a>, <a href="https://publications.waset.org/abstracts/search?q=Fourier%20series" title=" Fourier series"> Fourier series</a>, <a href="https://publications.waset.org/abstracts/search?q=Lebesgue%20integral" title=" Lebesgue integral"> Lebesgue integral</a>, <a href="https://publications.waset.org/abstracts/search?q=Lip%20%28alpha" title=" Lip (alpha"> Lip (alpha</a>, <a href="https://publications.waset.org/abstracts/search?q=r%29class" title="r)class">r)class</a>, <a href="https://publications.waset.org/abstracts/search?q=W%28L%28r%29" title=" W(L(r)"> W(L(r)</a>, <a href="https://publications.waset.org/abstracts/search?q=xi%28t%29%29class%20of%20%20functions" title="xi(t))class of functions">xi(t))class of functions</a> </p> <a href="https://publications.waset.org/abstracts/32235/degree-of-approximation-of-functions-by-product-means" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/32235.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">517</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19199</span> Particle Swarm Optimization and Quantum Particle Swarm Optimization to Multidimensional Function Approximation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Diogo%20Silva">Diogo Silva</a>, <a href="https://publications.waset.org/abstracts/search?q=Fadul%20Rodor"> Fadul Rodor</a>, <a href="https://publications.waset.org/abstracts/search?q=Carlos%20Moraes"> Carlos Moraes</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This work compares the results of multidimensional function approximation using two algorithms: the classical Particle Swarm Optimization (PSO) and the Quantum Particle Swarm Optimization (QPSO). These algorithms were both tested on three functions - The Rosenbrock, the Rastrigin, and the sphere functions - with different characteristics by increasing their number of dimensions. As a result, this study shows that the higher the function space, i.e. the larger the function dimension, the more evident the advantages of using the QPSO method compared to the PSO method in terms of performance and number of necessary iterations to reach the stop criterion. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=PSO" title="PSO">PSO</a>, <a href="https://publications.waset.org/abstracts/search?q=QPSO" title=" QPSO"> QPSO</a>, <a href="https://publications.waset.org/abstracts/search?q=function%20approximation" title=" function approximation"> function approximation</a>, <a href="https://publications.waset.org/abstracts/search?q=AI" title=" AI"> AI</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization" title=" optimization"> optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=multidimensional%20functions" title=" multidimensional functions"> multidimensional functions</a> </p> <a href="https://publications.waset.org/abstracts/81790/particle-swarm-optimization-and-quantum-particle-swarm-optimization-to-multidimensional-function-approximation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/81790.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">589</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19198</span> Identification of Wiener Model Using Iterative Schemes</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Vikram%20Saini">Vikram Saini</a>, <a href="https://publications.waset.org/abstracts/search?q=Lillie%20Dewan"> Lillie Dewan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents the iterative schemes based on Least square, Hierarchical Least Square and Stochastic Approximation Gradient method for the Identification of Wiener model with parametric structure. A gradient method is presented for the parameter estimation of wiener model with noise conditions based on the stochastic approximation. Simulation results are presented for the Wiener model structure with different static non-linear elements in the presence of colored noise to show the comparative analysis of the iterative methods. The stochastic gradient method shows improvement in the estimation performance and provides fast convergence of the parameters estimates. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=hard%20non-linearity" title="hard non-linearity">hard non-linearity</a>, <a href="https://publications.waset.org/abstracts/search?q=least%20square" title=" least square"> least square</a>, <a href="https://publications.waset.org/abstracts/search?q=parameter%20estimation" title=" parameter estimation"> parameter estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=stochastic%20approximation%20gradient" title=" stochastic approximation gradient"> stochastic approximation gradient</a>, <a href="https://publications.waset.org/abstracts/search?q=Wiener%20model" title=" Wiener model"> Wiener model</a> </p> <a href="https://publications.waset.org/abstracts/70632/identification-of-wiener-model-using-iterative-schemes" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/70632.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">405</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19197</span> Function Approximation with Radial Basis Function Neural Networks via FIR Filter</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kyu%20Chul%20Lee">Kyu Chul Lee</a>, <a href="https://publications.waset.org/abstracts/search?q=Sung%20Hyun%20Yoo"> Sung Hyun Yoo</a>, <a href="https://publications.waset.org/abstracts/search?q=Choon%20Ki%20Ahn"> Choon Ki Ahn</a>, <a href="https://publications.waset.org/abstracts/search?q=Myo%20Taeg%20Lim"> Myo Taeg Lim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Recent experimental evidences have shown that because of a fast convergence and a nice accuracy, neural networks training via extended Kalman filter (EKF) method is widely applied. However, as to an uncertainty of the system dynamics or modeling error, the performance of the method is unreliable. In order to overcome this problem in this paper, a new finite impulse response (FIR) filter based learning algorithm is proposed to train radial basis function neural networks (RBFN) for nonlinear function approximation. Compared to the EKF training method, the proposed FIR filter training method is more robust to those environmental conditions. Furthermore, the number of centers will be considered since it affects the performance of approximation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=extended%20Kalman%20filter" title="extended Kalman filter">extended Kalman filter</a>, <a href="https://publications.waset.org/abstracts/search?q=classification%20problem" title=" classification problem"> classification problem</a>, <a href="https://publications.waset.org/abstracts/search?q=radial%20basis%20function%20networks%20%28RBFN%29" title=" radial basis function networks (RBFN)"> radial basis function networks (RBFN)</a>, <a href="https://publications.waset.org/abstracts/search?q=finite%20impulse%20response%20%28FIR%29%20filter" title=" finite impulse response (FIR) filter"> finite impulse response (FIR) filter</a> </p> <a href="https://publications.waset.org/abstracts/13851/function-approximation-with-radial-basis-function-neural-networks-via-fir-filter" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/13851.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">456</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19196</span> An Improved Prediction Model of Ozone Concentration Time Series Based on Chaotic Approach </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nor%20Zila%20Abd%20Hamid">Nor Zila Abd Hamid</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohd%20Salmi%20M.%20Noorani"> Mohd Salmi M. Noorani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study is focused on the development of prediction models of the Ozone concentration time series. Prediction model is built based on chaotic approach. Firstly, the chaotic nature of the time series is detected by means of phase space plot and the Cao method. Then, the prediction model is built and the local linear approximation method is used for the forecasting purposes. Traditional prediction of autoregressive linear model is also built. Moreover, an improvement in local linear approximation method is also performed. Prediction models are applied to the hourly ozone time series observed at the benchmark station in Malaysia. Comparison of all models through the calculation of mean absolute error, root mean squared error and correlation coefficient shows that the one with improved prediction method is the best. Thus, chaotic approach is a good approach to be used to develop a prediction model for the Ozone concentration time series. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=chaotic%20approach" title="chaotic approach">chaotic approach</a>, <a href="https://publications.waset.org/abstracts/search?q=phase%20space" title=" phase space"> phase space</a>, <a href="https://publications.waset.org/abstracts/search?q=Cao%20method" title=" Cao method"> Cao method</a>, <a href="https://publications.waset.org/abstracts/search?q=local%20linear%20approximation%20method" title=" local linear approximation method"> local linear approximation method</a> </p> <a href="https://publications.waset.org/abstracts/2015/an-improved-prediction-model-of-ozone-concentration-time-series-based-on-chaotic-approach" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/2015.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">331</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19195</span> High Accuracy Analytic Approximation for Special Functions Applied to Bessel Functions J₀(x) and Its Zeros</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Fernando%20Maass">Fernando Maass</a>, <a href="https://publications.waset.org/abstracts/search?q=Pablo%20Martin"> Pablo Martin</a>, <a href="https://publications.waset.org/abstracts/search?q=Jorge%20Olivares"> Jorge Olivares</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Bessel function J₀(x) is very important in Electrodynamics and Physics, as well as its zeros. In this work, a method to obtain high accuracy approximation is presented through an application to that function. In most of the applications of this function, the values of the zeros are very important. In this work, analytic approximations for this function have been obtained valid for all positive values of the variable x, which have high accuracy for the function as well as for the zeros. The approximation is determined by the simultaneous used of the power series and asymptotic expansion. The structure of the approximation is a combination of two rational functions with elementary functions as trigonometric and fractional powers. Here us in Pade method, rational functions are used, but now there combined with elementary functions us fractional powers hyperbolic or trigonometric functions, and others. The reason of this is that now power series of the exact function are used, but together with the asymptotic expansion, which usually includes fractional powers trigonometric functions and other type of elementary functions. The approximation must be a bridge between both expansions, and this can not be accomplished using only with rational functions. In the simplest approximation using 4 parameters the maximum absolute error is less than 0.006 at x ∼ 4.9. In this case also the maximum relative error for the zeros is less than 0.003 which is for the second zero, but that value decreases rapidly for the other zeros. The same kind of behaviour happens for the relative error of the maximum and minimum of the functions. Approximations with higher accuracy and more parameters will be also shown. All the approximations are valid for any positive value of x, and they can be calculated easily. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=analytic%20approximations" title="analytic approximations">analytic approximations</a>, <a href="https://publications.waset.org/abstracts/search?q=asymptotic%20approximations" title=" asymptotic approximations"> asymptotic approximations</a>, <a href="https://publications.waset.org/abstracts/search?q=Bessel%20functions" title=" Bessel functions"> Bessel functions</a>, <a href="https://publications.waset.org/abstracts/search?q=quasirational%20approximations" title=" quasirational approximations"> quasirational approximations</a> </p> <a href="https://publications.waset.org/abstracts/92867/high-accuracy-analytic-approximation-for-special-functions-applied-to-bessel-functions-j0x-and-its-zeros" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/92867.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">251</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19194</span> Constant Factor Approximation Algorithm for p-Median Network Design Problem with Multiple Cable Types</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chaghoub%20Soraya">Chaghoub Soraya</a>, <a href="https://publications.waset.org/abstracts/search?q=Zhang%20Xiaoyan"> Zhang Xiaoyan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This research presents the first constant approximation algorithm to the p-median network design problem with multiple cable types. This problem was addressed with a single cable type and there is a bifactor approximation algorithm for the problem. To the best of our knowledge, the algorithm proposed in this paper is the first constant approximation algorithm for the p-median network design with multiple cable types. The addressed problem is a combination of two well studied problems which are p-median problem and network design problem. The introduced algorithm is a random sampling approximation algorithm of constant factor which is conceived by using some random sampling techniques form the literature. It is based on a redistribution Lemma from the literature and a steiner tree problem as a subproblem. This algorithm is simple, and it relies on the notions of random sampling and probability. The proposed approach gives an approximation solution with one constant ratio without violating any of the constraints, in contrast to the one proposed in the literature. This paper provides a (21 + 2)-approximation algorithm for the p-median network design problem with multiple cable types using random sampling techniques. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=approximation%20algorithms" title="approximation algorithms">approximation algorithms</a>, <a href="https://publications.waset.org/abstracts/search?q=buy-at-bulk" title=" buy-at-bulk"> buy-at-bulk</a>, <a href="https://publications.waset.org/abstracts/search?q=combinatorial%20optimization" title=" combinatorial optimization"> combinatorial optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=network%20design" title=" network design"> network design</a>, <a href="https://publications.waset.org/abstracts/search?q=p-median" title=" p-median"> p-median</a> </p> <a href="https://publications.waset.org/abstracts/127337/constant-factor-approximation-algorithm-for-p-median-network-design-problem-with-multiple-cable-types" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/127337.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">203</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19193</span> An Optimized RDP Algorithm for Curve Approximation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jean-Pierre%20Lomaliza">Jean-Pierre Lomaliza</a>, <a href="https://publications.waset.org/abstracts/search?q=Kwang-Seok%20Moon"> Kwang-Seok Moon</a>, <a href="https://publications.waset.org/abstracts/search?q=Hanhoon%20Park"> Hanhoon Park</a> </p> <p class="card-text"><strong>Abstract:</strong></p> It is well-known that Ramer Douglas Peucker (RDP) algorithm greatly depends on the method of choosing starting points. Therefore, this paper focuses on finding such starting points that will optimize the results of RDP algorithm. Specifically, this paper proposes a curve approximation algorithm that finds flat points, called essential points, of an input curve, divides the curve into corner-like sub-curves using the essential points, and applies the RDP algorithm to the sub-curves. The number of essential points play a role on optimizing the approximation results by balancing the degree of shape information loss and the amount of data reduction. Through experiments with curves of various types and complexities of shape, we compared the performance of the proposed algorithm with three other methods, i.e., the RDP algorithm itself and its variants. As a result, the proposed algorithm outperformed the others in term of maintaining the original shapes of the input curve, which is important in various applications like pattern recognition. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=curve%20approximation" title="curve approximation">curve approximation</a>, <a href="https://publications.waset.org/abstracts/search?q=essential%20point" title=" essential point"> essential point</a>, <a href="https://publications.waset.org/abstracts/search?q=RDP%20algorithm" title=" RDP algorithm"> RDP algorithm</a> </p> <a href="https://publications.waset.org/abstracts/29359/an-optimized-rdp-algorithm-for-curve-approximation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/29359.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">535</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19192</span> Approximation of Periodic Functions Belonging to Lipschitz Classes by Product Matrix Means of Fourier Series</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Smita%20Sonker">Smita Sonker</a>, <a href="https://publications.waset.org/abstracts/search?q=Uaday%20Singh"> Uaday Singh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Various investigators have determined the degree of approximation of functions belonging to the classes W(L r , ξ(t)), Lip(ξ(t), r), Lip(α, r), and Lipα using different summability methods with monotonocity conditions. Recently, Lal has determined the degree of approximation of the functions belonging to Lipα and W(L r , ξ(t)) classes by using Ces`aro-N¨orlund (C 1 .Np)- summability with non-increasing weights {pn}. In this paper, we shall determine the degree of approximation of 2π - periodic functions f belonging to the function classes Lipα and W(L r , ξ(t)) by C 1 .T - means of Fourier series of f. Our theorems generalize the results of Lal and we also improve these results in the light off. From our results, we also derive some corollaries. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Lipschitz%20classes" title="Lipschitz classes">Lipschitz classes</a>, <a href="https://publications.waset.org/abstracts/search?q=product%20matrix%20operator" title=" product matrix operator"> product matrix operator</a>, <a href="https://publications.waset.org/abstracts/search?q=signals" title=" signals"> signals</a>, <a href="https://publications.waset.org/abstracts/search?q=trigonometric%20Fourier%20approximation" title=" trigonometric Fourier approximation"> trigonometric Fourier approximation</a> </p> <a href="https://publications.waset.org/abstracts/4757/approximation-of-periodic-functions-belonging-to-lipschitz-classes-by-product-matrix-means-of-fourier-series" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/4757.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">477</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19191</span> The Improved Element Free Galerkin Method for 2D Heat Transfer Problems</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Imen%20Debbabi">Imen Debbabi</a>, <a href="https://publications.waset.org/abstracts/search?q=H%C3%A9di%20BelHadjSalah"> Hédi BelHadjSalah</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Improved Element Free Galerkin (IEFG) method is presented to treat the steady states and the transient heat transfer problems. As a result of a combination between the Improved Moving Least Square (IMLS) approximation and the Element Free Galerkin (EFG) method, the IEFG's shape functions don't have the Kronecker delta property and the penalty method is used to impose the Dirichlet boundary conditions. In this paper, two heat transfer problems, transient and steady states, are studied to improve the efficiency of this meshfree method for 2D heat transfer problems. The performance of the IEFG method is shown using the comparison between numerical and analytic results. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=meshfree%20methods" title="meshfree methods">meshfree methods</a>, <a href="https://publications.waset.org/abstracts/search?q=the%20Improved%20Moving%20Least%20Square%20approximation%20%28IMLS%29" title=" the Improved Moving Least Square approximation (IMLS)"> the Improved Moving Least Square approximation (IMLS)</a>, <a href="https://publications.waset.org/abstracts/search?q=the%20Improved%20Element%20Free%20Galerkin%20method%20%28IEFG%29" title=" the Improved Element Free Galerkin method (IEFG)"> the Improved Element Free Galerkin method (IEFG)</a>, <a href="https://publications.waset.org/abstracts/search?q=heat%20transfer%20problems" title=" heat transfer problems"> heat transfer problems</a> </p> <a href="https://publications.waset.org/abstracts/47458/the-improved-element-free-galerkin-method-for-2d-heat-transfer-problems" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/47458.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">393</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19190</span> Bayesian Analysis of Topp-Leone Generalized Exponential Distribution</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Najrullah%20Khan">Najrullah Khan</a>, <a href="https://publications.waset.org/abstracts/search?q=Athar%20Ali%20Khan"> Athar Ali Khan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Topp-Leone distribution was introduced by Topp- Leone in 1955. In this paper, an attempt has been made to fit Topp-Leone Generalized exponential (TPGE) distribution. A real survival data set is used for illustrations. Implementation is done using R and JAGS and appropriate illustrations are made. R and JAGS codes have been provided to implement censoring mechanism using both optimization and simulation tools. The main aim of this paper is to describe and illustrate the Bayesian modelling approach to the analysis of survival data. Emphasis is placed on the modeling of data and the interpretation of the results. Crucial to this is an understanding of the nature of the incomplete or 'censored' data encountered. Analytic approximation and simulation tools are covered here, but most of the emphasis is on Markov chain based Monte Carlo method including independent Metropolis algorithm, which is currently the most popular technique. For analytic approximation, among various optimization algorithms and trust region method is found to be the best. In this paper, TPGE model is also used to analyze the lifetime data in Bayesian paradigm. Results are evaluated from the above mentioned real survival data set. The analytic approximation and simulation methods are implemented using some software packages. It is clear from our findings that simulation tools provide better results as compared to those obtained by asymptotic approximation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bayesian%20Inference" title="Bayesian Inference">Bayesian Inference</a>, <a href="https://publications.waset.org/abstracts/search?q=JAGS" title=" JAGS"> JAGS</a>, <a href="https://publications.waset.org/abstracts/search?q=Laplace%20Approximation" title=" Laplace Approximation"> Laplace Approximation</a>, <a href="https://publications.waset.org/abstracts/search?q=LaplacesDemon" title=" LaplacesDemon"> LaplacesDemon</a>, <a href="https://publications.waset.org/abstracts/search?q=posterior" title=" posterior"> posterior</a>, <a href="https://publications.waset.org/abstracts/search?q=R%20Software" title=" R Software"> R Software</a>, <a href="https://publications.waset.org/abstracts/search?q=simulation" title=" simulation"> simulation</a> </p> <a href="https://publications.waset.org/abstracts/77532/bayesian-analysis-of-topp-leone-generalized-exponential-distribution" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/77532.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">535</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19189</span> The Modelling of Real Time Series Data</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Valeria%20Bondarenko">Valeria Bondarenko</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We proposed algorithms for: estimation of parameters fBm (volatility and Hurst exponent) and for the approximation of random time series by functional of fBm. We proved the consistency of the estimators, which constitute the above algorithms, and proved the optimal forecast of approximated time series. The adequacy of estimation algorithms, approximation, and forecasting is proved by numerical experiment. During the process of creating software, the system has been created, which is displayed by the hierarchical structure. The comparative analysis of proposed algorithms with the other methods gives evidence of the advantage of approximation method. The results can be used to develop methods for the analysis and modeling of time series describing the economic, physical, biological and other processes. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=mathematical%20model" title="mathematical model">mathematical model</a>, <a href="https://publications.waset.org/abstracts/search?q=random%20process" title=" random process"> random process</a>, <a href="https://publications.waset.org/abstracts/search?q=Wiener%20process" title=" Wiener process"> Wiener process</a>, <a href="https://publications.waset.org/abstracts/search?q=fractional%20Brownian%20motion" title=" fractional Brownian motion"> fractional Brownian motion</a> </p> <a href="https://publications.waset.org/abstracts/49210/the-modelling-of-real-time-series-data" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/49210.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">357</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19188</span> A Hybrid Adomian Decomposition Method in the Solution of Logistic Abelian Ordinary Differential and Its Comparism with Some Standard Numerical Scheme</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=F.%20J.%20Adeyeye">F. J. Adeyeye</a>, <a href="https://publications.waset.org/abstracts/search?q=D.%20Eni"> D. Eni</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20M.%20Okedoye"> K. M. Okedoye</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper we present a Hybrid of Adomian decomposition method (ADM). This is the substitution of a One-step method of Taylor’s series approximation of orders I and II, into the nonlinear part of Adomian decomposition method resulting in a convergent series scheme. This scheme is applied to solve some Logistic problems represented as Abelian differential equation and the results are compared with the actual solution and Runge-kutta of order IV in order to ascertain the accuracy and efficiency of the scheme. The findings shows that the scheme is efficient enough to solve logistic problems considered in this paper. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Adomian%20decomposition%20method" title="Adomian decomposition method">Adomian decomposition method</a>, <a href="https://publications.waset.org/abstracts/search?q=nonlinear%20part" title=" nonlinear part"> nonlinear part</a>, <a href="https://publications.waset.org/abstracts/search?q=one-step%20method" title=" one-step method"> one-step method</a>, <a href="https://publications.waset.org/abstracts/search?q=Taylor%20series%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20approximation" title=" Taylor series approximation"> Taylor series approximation</a>, <a href="https://publications.waset.org/abstracts/search?q=hybrid%20of%20Adomian%20polynomial" title=" hybrid of Adomian polynomial"> hybrid of Adomian polynomial</a>, <a href="https://publications.waset.org/abstracts/search?q=logistic%20problem" title=" logistic problem"> logistic problem</a>, <a href="https://publications.waset.org/abstracts/search?q=Malthusian%20parameter" title=" Malthusian parameter"> Malthusian parameter</a>, <a href="https://publications.waset.org/abstracts/search?q=Verhulst%20Model" title=" Verhulst Model"> Verhulst Model</a> </p> <a href="https://publications.waset.org/abstracts/36872/a-hybrid-adomian-decomposition-method-in-the-solution-of-logistic-abelian-ordinary-differential-and-its-comparism-with-some-standard-numerical-scheme" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/36872.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">400</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19187</span> Bayesian Using Markov Chain Monte Carlo and Lindley's Approximation Based on Type-I Censored Data</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Al%20Omari%20Moahmmed%20Ahmed">Al Omari Moahmmed Ahmed</a> </p> <p class="card-text"><strong>Abstract:</strong></p> These papers describe the Bayesian Estimator using Markov Chain Monte Carlo and Lindley’s approximation and the maximum likelihood estimation of the Weibull distribution with Type-I censored data. The maximum likelihood method can’t estimate the shape parameter in closed forms, although it can be solved by numerical methods. Moreover, the Bayesian estimates of the parameters, the survival and hazard functions cannot be solved analytically. Hence Markov Chain Monte Carlo method and Lindley’s approximation are used, where the full conditional distribution for the parameters of Weibull distribution are obtained via Gibbs sampling and Metropolis-Hastings algorithm (HM) followed by estimate the survival and hazard functions. The methods are compared to Maximum Likelihood counterparts and the comparisons are made with respect to the Mean Square Error (MSE) and absolute bias to determine the better method in scale and shape parameters, the survival and hazard functions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=weibull%20distribution" title="weibull distribution">weibull distribution</a>, <a href="https://publications.waset.org/abstracts/search?q=bayesian%20method" title=" bayesian method"> bayesian method</a>, <a href="https://publications.waset.org/abstracts/search?q=markov%20chain%20mote%20carlo" title=" markov chain mote carlo"> markov chain mote carlo</a>, <a href="https://publications.waset.org/abstracts/search?q=survival%20and%20hazard%20functions" title=" survival and hazard functions"> survival and hazard functions</a> </p> <a href="https://publications.waset.org/abstracts/31291/bayesian-using-markov-chain-monte-carlo-and-lindleys-approximation-based-on-type-i-censored-data" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/31291.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">479</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19186</span> Approximation of Convex Set by Compactly Semidefinite Representable Set</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Anusuya%20Ghosh">Anusuya Ghosh</a>, <a href="https://publications.waset.org/abstracts/search?q=Vishnu%20Narayanan"> Vishnu Narayanan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The approximation of convex set by semidefinite representable set plays an important role in semidefinite programming, especially in modern convex optimization. To optimize a linear function over a convex set is a hard problem. But optimizing the linear function over the semidefinite representable set which approximates the convex set is easy to solve as there exists numerous efficient algorithms to solve semidefinite programming problems. So, our approximation technique is significant in optimization. We develop a technique to approximate any closed convex set, say K by compactly semidefinite representable set. Further we prove that there exists a sequence of compactly semidefinite representable sets which give tighter approximation of the closed convex set, K gradually. We discuss about the convergence of the sequence of compactly semidefinite representable sets to closed convex set K. The recession cone of K and the recession cone of the compactly semidefinite representable set are equal. So, we say that the sequence of compactly semidefinite representable sets converge strongly to the closed convex set. Thus, this approximation technique is very useful development in semidefinite programming. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=semidefinite%20programming" title="semidefinite programming">semidefinite programming</a>, <a href="https://publications.waset.org/abstracts/search?q=semidefinite%20representable%20set" title=" semidefinite representable set"> semidefinite representable set</a>, <a href="https://publications.waset.org/abstracts/search?q=compactly%20semidefinite%20representable%20set" title=" compactly semidefinite representable set"> compactly semidefinite representable set</a>, <a href="https://publications.waset.org/abstracts/search?q=approximation" title=" approximation"> approximation</a> </p> <a href="https://publications.waset.org/abstracts/36914/approximation-of-convex-set-by-compactly-semidefinite-representable-set" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/36914.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">386</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19185</span> Approximation of Analytic Functions of Several Variables by Linear K-Positive Operators in the Closed Domain</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tulin%20Coskun">Tulin Coskun</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We investigate the approximation of analytic functions of several variables in polydisc by the sequences of linear k-positive operators in Gadjiev sence. The approximation of analytic functions of complex variable by linear k-positive operators was tackled, and k-positive operators and formulated theorems of Korovkin's type for these operators in the space of analytic functions on the unit disc were introduced in the past. Recently, very general results on convergence of the sequences of linear k-positive operators on a simply connected bounded domain within the space of analytic functions were proved. In this presentation, we extend some of these results to the approximation of analytic functions of several complex variables by sequences of linear k-positive operators. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=analytic%20functions" title="analytic functions">analytic functions</a>, <a href="https://publications.waset.org/abstracts/search?q=approximation%20of%20analytic%20functions" title=" approximation of analytic functions"> approximation of analytic functions</a>, <a href="https://publications.waset.org/abstracts/search?q=Linear%20k-positive%20operators" title=" Linear k-positive operators"> Linear k-positive operators</a>, <a href="https://publications.waset.org/abstracts/search?q=Korovkin%20type%20theorems" title=" Korovkin type theorems"> Korovkin type theorems</a> </p> <a href="https://publications.waset.org/abstracts/53219/approximation-of-analytic-functions-of-several-variables-by-linear-k-positive-operators-in-the-closed-domain" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/53219.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">338</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19184</span> Approximation to the Hardy Operator on Topological Measure Spaces</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kairat%20T.%20Mynbaev">Kairat T. Mynbaev</a>, <a href="https://publications.waset.org/abstracts/search?q=Elena%20N.%20Lomakina"> Elena N. Lomakina</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We consider a Hardy-type operator generated by a family of open subsets of a Hausdorff topological space. The family is indexed with non-negative real numbers and is totally ordered. For this operator, we obtain two-sided bounds of its norm, a compactness criterion, and bounds for its approximation numbers. Previously, bounds for its approximation numbers have been established only in the one-dimensional case, while we do not impose any restrictions on the dimension of the Hausdorff space. The bounds for the norm and conditions for compactness earlier have been found using different methods by G. Sinnamon and K. Mynbaev. Our approach is different in that we use domain partitions for all problems under consideration. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=approximation%20numbers" title="approximation numbers">approximation numbers</a>, <a href="https://publications.waset.org/abstracts/search?q=boundedness%20and%20compactness" title=" boundedness and compactness"> boundedness and compactness</a>, <a href="https://publications.waset.org/abstracts/search?q=multidimensional%20Hardy%20operator" title=" multidimensional Hardy operator"> multidimensional Hardy operator</a>, <a href="https://publications.waset.org/abstracts/search?q=Hausdorff%20topological%20space" title=" Hausdorff topological space"> Hausdorff topological space</a> </p> <a href="https://publications.waset.org/abstracts/170957/approximation-to-the-hardy-operator-on-topological-measure-spaces" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/170957.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">104</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19183</span> Degree of Approximation by the (T.E^1) Means of Conjugate Fourier Series in the Hölder Metric</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kejal%20Khatri">Kejal Khatri</a>, <a href="https://publications.waset.org/abstracts/search?q=Vishnu%20Narayan%20Mishra"> Vishnu Narayan Mishra</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We compute the degree of approximation of functions\tilde{f}\in H_w, a new Banach space using (T.E^1) summability means of conjugate Fourier series. In this paper, we extend the results of Singh and Mahajan which in turn generalizes the result of Lal and Yadav. Some corollaries have also been deduced from our main theorem and particular cases. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=conjugate%20Fourier%20series" title="conjugate Fourier series">conjugate Fourier series</a>, <a href="https://publications.waset.org/abstracts/search?q=degree%20of%20approximation" title=" degree of approximation"> degree of approximation</a>, <a href="https://publications.waset.org/abstracts/search?q=H%C3%B6lder%20metric" title=" Hölder metric"> Hölder metric</a>, <a href="https://publications.waset.org/abstracts/search?q=matrix%20summability" title=" matrix summability"> matrix summability</a>, <a href="https://publications.waset.org/abstracts/search?q=product%20summability" title=" product summability"> product summability</a> </p> <a href="https://publications.waset.org/abstracts/2123/degree-of-approximation-by-the-te1-means-of-conjugate-fourier-series-in-the-holder-metric" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/2123.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">419</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19182</span> Model Order Reduction for Frequency Response and Effect of Order of Method for Matching Condition</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Aref%20Ghafouri">Aref Ghafouri</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20javad%20Mollakazemi"> Mohammad javad Mollakazemi</a>, <a href="https://publications.waset.org/abstracts/search?q=Farhad%20Asadi"> Farhad Asadi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, model order reduction method is used for approximation in linear and nonlinearity aspects in some experimental data. This method can be used for obtaining offline reduced model for approximation of experimental data and can produce and follow the data and order of system and also it can match to experimental data in some frequency ratios. In this study, the method is compared in different experimental data and influence of choosing of order of the model reduction for obtaining the best and sufficient matching condition for following the data is investigated in format of imaginary and reality part of the frequency response curve and finally the effect and important parameter of number of order reduction in nonlinear experimental data is explained further. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=frequency%20response" title="frequency response">frequency response</a>, <a href="https://publications.waset.org/abstracts/search?q=order%20of%20model%20reduction" title=" order of model reduction"> order of model reduction</a>, <a href="https://publications.waset.org/abstracts/search?q=frequency%20matching%20condition" title=" frequency matching condition"> frequency matching condition</a>, <a href="https://publications.waset.org/abstracts/search?q=nonlinear%20experimental%20data" title=" nonlinear experimental data"> nonlinear experimental data</a> </p> <a href="https://publications.waset.org/abstracts/17631/model-order-reduction-for-frequency-response-and-effect-of-order-of-method-for-matching-condition" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/17631.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">402</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19181</span> A Nonlinear Parabolic Partial Differential Equation Model for Image Enhancement</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tudor%20Barbu">Tudor Barbu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We present a robust nonlinear parabolic partial differential equation (PDE)-based denoising scheme in this article. Our approach is based on a second-order anisotropic diffusion model that is described first. Then, a consistent and explicit numerical approximation algorithm is constructed for this continuous model by using the finite-difference method. Finally, our restoration experiments and method comparison, which prove the effectiveness of this proposed technique, are discussed in this paper. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=anisotropic%20diffusion" title="anisotropic diffusion">anisotropic diffusion</a>, <a href="https://publications.waset.org/abstracts/search?q=finite%20differences" title=" finite differences"> finite differences</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20denoising%20and%20restoration" title=" image denoising and restoration"> image denoising and restoration</a>, <a href="https://publications.waset.org/abstracts/search?q=nonlinear%20PDE%20model" title=" nonlinear PDE model"> nonlinear PDE model</a>, <a href="https://publications.waset.org/abstracts/search?q=anisotropic%20diffusion" title=" anisotropic diffusion"> anisotropic diffusion</a>, <a href="https://publications.waset.org/abstracts/search?q=numerical%20approximation%20schemes" title=" numerical approximation schemes"> numerical approximation schemes</a> </p> <a href="https://publications.waset.org/abstracts/48289/a-nonlinear-parabolic-partial-differential-equation-model-for-image-enhancement" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/48289.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">312</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19180</span> On the PTC Thermistor Model with a Hyperbolic Tangent Electrical Conductivity</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20O.%20Durojaye">M. O. Durojaye</a>, <a href="https://publications.waset.org/abstracts/search?q=J.%20T.%20Agee"> J. T. Agee</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper is on the one-dimensional, positive temperature coefficient (PTC) thermistor model with a hyperbolic tangent function approximation for the electrical conductivity. The method of asymptotic expansion was adopted to obtain the steady state solution and the unsteady-state response was obtained using the method of lines (MOL) which is a well-established numerical technique. The approach is to reduce the partial differential equation to a vector system of ordinary differential equations and solve numerically. Our analysis shows that the hyperbolic tangent approximation introduced is well suitable for the electrical conductivity. Numerical solutions obtained also exhibit correct physical characteristics of the thermistor and are in good agreement with the exact steady state solutions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=electrical%20conductivity" title="electrical conductivity">electrical conductivity</a>, <a href="https://publications.waset.org/abstracts/search?q=hyperbolic%20tangent%20function" title=" hyperbolic tangent function"> hyperbolic tangent function</a>, <a href="https://publications.waset.org/abstracts/search?q=PTC%20thermistor" title=" PTC thermistor"> PTC thermistor</a>, <a href="https://publications.waset.org/abstracts/search?q=method%20of%20lines" title=" method of lines"> method of lines</a> </p> <a href="https://publications.waset.org/abstracts/44120/on-the-ptc-thermistor-model-with-a-hyperbolic-tangent-electrical-conductivity" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/44120.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">322</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19179</span> Property and Inheritance Rights for Women Whose Husbands Disappeared during the Last War in Kosovo: Case Studies: Krusha e Vogël and Krusha e Madhe, Region of Prizren, Kosovo</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Venera%20Goxha">Venera Goxha</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Property and inheritance rights for women whose husbands were killed or disappeared during the last war in Kosovo is the purpose of this study, respectively, the access of these women to family real estate. The case study is about women whose husbands were killed or disappeared during the last war in Kosovo and who, on this occasion, earned the title of 'widow'.The research is conducted in the villages of Krusha e Vogël - Municipality of Prizren, and Krusha e Madhe - Municipality of Rahovec, one of the most suffered villages from the recent war in Kosovo. Krusha e Vogël, as a result of the recent war, has 113 male victims, or 70% of all men from the age of 13 to the age of 77, leaving widows and orphans. In the village of Krusha e Madhe, 243 Albanians were massacred by Serbs living in the same village, leaving widows and orphaned children alive. According to these data, most of the Krushian families, as heads of households, have surviving wives and widows. Therefore, being the head of the family and facing a mountain of challenges, such as economic, social, and cultural, the issue of how these women have approached the property and family heritage is considered. The equal right to property and inheritance is a right that is guaranteed to women with all legislation in force, starting from the Constitution of the Republic of Kosovo onwards. Article 7 of the Constitution of Kosovo and the subsequent legal framework recognizes the equality of women and the equal division of property between heirs, daughters, and sons. However, some of the legislation does not successfully reflect the current reality in Kosovo. All these ambiguities follow from the ‘patriarchal law’ of the Albanians in the time of the early Middle Ages, later known as the ‘Kanun of Lekë Dukagjini’. At the time it was written and applied, it weighted the law in force, but later over time, it passed into tradition, culture, and mentality. The Kanun of Lekë Dukagjini, in no context, has treated women equally to men. The female, according to the Kanun, was a working tool, a creature to be born, to work, to carry, to raise children, and to remain faithful to the husband even when the husband is not faithful. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=property%20rights" title="property rights">property rights</a>, <a href="https://publications.waset.org/abstracts/search?q=heritage" title=" heritage"> heritage</a>, <a href="https://publications.waset.org/abstracts/search?q=widows" title=" widows"> widows</a>, <a href="https://publications.waset.org/abstracts/search?q=code" title=" code"> code</a> </p> <a href="https://publications.waset.org/abstracts/146678/property-and-inheritance-rights-for-women-whose-husbands-disappeared-during-the-last-war-in-kosovo-case-studies-krusha-e-vogel-and-krusha-e-madhe-region-of-prizren-kosovo" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/146678.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">61</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19178</span> Application of Wavelet Based Approximation for the Solution of Partial Integro-Differential Equation Arising from Viscoelasticity</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Somveer%20Singh">Somveer Singh</a>, <a href="https://publications.waset.org/abstracts/search?q=Vineet%20Kumar%20Singh"> Vineet Kumar Singh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This work contributes a numerical method based on Legendre wavelet approximation for the treatment of partial integro-differential equation (PIDE). Operational matrices of Legendre wavelets reduce the solution of PIDE into the system of algebraic equations. Some useful results concerning the computational order of convergence and error estimates associated to the suggested scheme are presented. Illustrative examples are provided to show the effectiveness and accuracy of proposed numerical method. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=legendre%20wavelets" title="legendre wavelets">legendre wavelets</a>, <a href="https://publications.waset.org/abstracts/search?q=operational%20matrices" title=" operational matrices"> operational matrices</a>, <a href="https://publications.waset.org/abstracts/search?q=partial%20integro-differential%20equation" title=" partial integro-differential equation"> partial integro-differential equation</a>, <a href="https://publications.waset.org/abstracts/search?q=viscoelasticity" title=" viscoelasticity"> viscoelasticity</a> </p> <a href="https://publications.waset.org/abstracts/57515/application-of-wavelet-based-approximation-for-the-solution-of-partial-integro-differential-equation-arising-from-viscoelasticity" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/57515.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">448</span> </span> </div> </div> <ul class="pagination"> <li class="page-item disabled"><span class="page-link">&lsaquo;</span></li> <li class="page-item active"><span class="page-link">1</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=Vogel%E2%80%99s%20approximation%20method&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=Vogel%E2%80%99s%20approximation%20method&page=3">3</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=Vogel%E2%80%99s%20approximation%20method&page=4">4</a></li> <li class="page-item"><a class="page-link" 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