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Design of Geochemical Maps of Industrial City Using Gradient Boosting and Geographic Information System
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</div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 87480</div> </div> </div> </div> <div class="card publication-listing mt-3 mb-3"> <h5 class="card-header" style="font-size:.9rem">Design of Geochemical Maps of Industrial City Using Gradient Boosting and Geographic Information System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ruslan%20Safarov">Ruslan Safarov</a>, <a href="https://publications.waset.org/abstracts/search?q=Zhanat%20Shomanova"> Zhanat Shomanova</a>, <a href="https://publications.waset.org/abstracts/search?q=Yuri%20Nossenko"> Yuri Nossenko</a>, <a href="https://publications.waset.org/abstracts/search?q=Zhandos%20Mussayev"> Zhandos Mussayev</a>, <a href="https://publications.waset.org/abstracts/search?q=Ayana%20Baltabek"> Ayana Baltabek</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Geochemical maps of distribution of polluting elements V, Cr, Mn, Co, Ni, Cu, Zn, Mo, Cd, Pb on the territory of the Pavlodar city (Kazakhstan), which is an industrial hub were designed. The samples of soil were taken from 100 locations. Elemental analysis has been performed using XRF. The obtained data was used for training of the computational model with gradient boosting algorithm. The optimal parameters of model as well as the loss function were selected. The computational model was used for prediction of polluting elements concentration for 1000 evenly distributed points. Based on predicted data geochemical maps were created. Additionally, the total pollution index Zc was calculated for every from 1000 point. The spatial distribution of the Zc index was visualized using GIS (QGIS). It was calculated that the maximum coverage area of the territory of the Pavlodar city belongs to the moderately hazardous category (89.7%). The visualization of the obtained data allowed us to conclude that the main source of contamination goes from the industrial zones where the strategic metallurgical and refining plants are placed. <iframe src="https://publications.waset.org/abstracts/163141.pdf" style="width:100%; height:400px;" frameborder="0"></iframe> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Pavlodar" title="Pavlodar">Pavlodar</a>, <a href="https://publications.waset.org/abstracts/search?q=geochemical%20map" title=" geochemical map"> geochemical map</a>, <a href="https://publications.waset.org/abstracts/search?q=gradient%20boosting" title=" gradient boosting"> gradient boosting</a>, <a href="https://publications.waset.org/abstracts/search?q=CatBoost" title=" CatBoost"> CatBoost</a>, <a href="https://publications.waset.org/abstracts/search?q=QGIS" title=" QGIS"> QGIS</a>, <a href="https://publications.waset.org/abstracts/search?q=spatial%20distribution" title=" spatial distribution"> spatial distribution</a>, <a href="https://publications.waset.org/abstracts/search?q=heavy%20metals" title=" heavy metals"> heavy metals</a> </p> <a href="https://publications.waset.org/abstracts/163141/design-of-geochemical-maps-of-industrial-city-using-gradient-boosting-and-geographic-information-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/163141.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">82</span> </span> </div> </div> </div> </main> <footer> <div id="infolinks" class="pt-3 pb-2"> <div class="container"> <div style="background-color:#f5f5f5;" class="p-3"> <div class="row"> <div class="col-md-2"> <ul class="list-unstyled"> About <li><a href="https://waset.org/page/support">About Us</a></li> <li><a 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