[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-125082-en":3,"doc-seo-125082-105":29,"detail-sidebar-cat-0-en-105":90},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":11,"language":21,"language_code":22,"site_id":23,"html_lang":22,"table_of_contents":24,"faqs":25,"seo_title":26,"seo_description":14,"update_tm":27,"read_time":28},125082,687197207639,"Asher","https://ap-avatar.wpscdn.com/davatar_a8503ba1806abce46bf441b54a3ca4cd",8,"Research & Report","Where to Build Food Banks - A Machine Learning Approach","Over 44 million Americans experience food insecurity, including 13 million children, and the condition contributes to physical and developmental harms as well as barriers to medical care, housing, and education. Food banks and pantries serve as critical support, yet many households face limited access due to transportation and insufficient service locations. This work builds a machine learning framework to optimize food bank placement using K-means clustering with income-aware weighting, evaluating results against Feeding America sites.","WHERE TO BUILD FOOD BANKS  \nA Machine Learning Approach  \nAbstract  \nOver 44 million Americans currently suffer from food insecurity, of whom 13 million are children. Food insecurity has been shown to cause a wide range of both physical and developmental issues. Across the United States, thousands of food banks and pantries serve as vital sources of food and other forms of aid for food-insecure families. By optimizing food bank locations, food banks and their resources would become more accessible to families who desperately require it. The aim of this paper is to build a machine learning framework that is able to optimize food bank locationsand to consider factors such as median income. We utilized the K-means clustering algorithm for this purpose due to its high processing speed and ability to factor in large amounts of data, as well as its unsupervised nature that doesn’t require training time or labeled training data. Our proposed method applies K-means over a range of houses sourced from California and Indiana U.S. Census and geospatial data, with a weighted K-means algorithm applied when income data is available. We generated food bank locations that aimed to prioritize lower income households and compared these locations against real food banks affiliated with Feeding America. Our results show that not only is K-means extremely fast, but our food bank locations were on average better than those of existing ones, saving distance between food banks and houses in both California and Indiana.  \nKeywords  \nmachine learning, K-means, food banks, food insecurity, geostatistics, clustering  \nStudent Author  \nGavin Ruan is a senior at West Lafayette Jr. Sr. High School anda non-degree-seeking student at Purdue University, where he takes courses from the Departments of Computer Science and Mathematics. He has been working with Professor Lin and Ziqi Guo on “Where to Build Food Banks: A Machine Learning Approach” since August 2022. With this research, he qualified to enter the 2023 Regeneron International Science and Engineering Fair, winning a special award from the Central Intelligence Agency, and he became a National STEM Champion through the nationwide National STEM Challenge, co-sponsored by the U.S. Department of Education. He credits this project for further developing his interests in research, currently focused in the areas of operations research, geospatial optimization, data science, and statistics.  \nMentors  \nZiqi Guo is a PhD candidate in Mechanical Engineering at Purdue University. His research focus is on machine learning, energy transport, and physical simulation. He got his bachelor’s degree in Energy and Power Engineering from Huazhong University of Science and Technology in 2021.  \nGuang Lin received his MS and PhD degrees in applied mathematics from Brown University in 2004 and 2007, respectively. He is currently the Associate Dean for Research & Innovation at the College of Science, Director of the Data Science Consulting Service, and a Full Professor with the Department of Mathematics, School of Mechanical Engineering, Purdue University. He has had in-depth involvement in developing deep learning and uncertainty quantification tools for a large variety of domains including energy and the environment. His research interests include diverse topics in computational science on both algorithms and applications, uncertainty quantification, large-scale data analysis, and multiscale modeling in a large variety of domains.  \nINTRODUCTION  \nFood insecurity continues to remain a longstanding challenge in the United States, with over 44 million food-insecure people in 2023, 13 million of whom were children (USDA ERS, n.d.) . Hunger has been linked to health issues including diabetes, high blood pressure, and heart disease (Carlson, 1916) . In children, food insecurity is linked with increased cases of asthma, anemia, anxiety, and aggression (Feeding America, n.d.) . In addition to health problems, food insecurity is esp","cbCait3wkUnNk4n1","https://ap.wps.com/l/cbCait3wkUnNk4n1","pdf",4728581,1,"English","en",105,"# Abstract\n# Introduction\n## Food insecurity and health impacts\n## Role of food banks and access barriers\n## Facility location and clustering background","[{\"question\":\"Why is optimizing food bank locations important?\",\"answer\":\"Food banks are vital for food-insecure families, but lack of transportation and available service locations limits access. Optimizing locations can improve coverage and reduce the distance between households and aid resources.\"},{\"question\":\"What machine learning method does the paper use?\",\"answer\":\"The paper uses the K-means clustering algorithm. It leverages its speed and ability to process large datasets without requiring labeled training data.\"},{\"question\":\"How does the approach handle income-related factors?\",\"answer\":\"A weighted K-means variant is applied when income data is available, aiming to prioritize lower-income households when generating candidate food bank locations.\"}]","Where to Build Food Banks - A Machine Learning Approach | PDF",1785896526,20,{"code":4,"msg":30,"data":31},"ok",{"site_id":23,"language":22,"slug":32,"title":13,"keywords":33,"description":14,"schema_data":34,"social_meta":85,"head_meta":87,"extra_data":89,"updated_unix":27},"where-to-build-food-banks-a-machine-learning-approach","",{"@graph":35,"@context":84},[36,53,67],{"@type":37,"itemListElement":38},"BreadcrumbList",[39,43,47,50],{"item":40,"name":41,"@type":42,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":44,"name":45,"@type":42,"position":46},"https://docshare.wps.com/document/","Document",2,{"item":48,"name":12,"@type":42,"position":49},"https://docshare.wps.com/document/research-report/",3,{"item":51,"name":13,"@type":42,"position":52},"https://docshare.wps.com/document/where-to-build-food-banks-a-machine-learning-approach/125082/",4,{"url":51,"name":13,"@type":54,"author":55,"headline":13,"publisher":57,"fileFormat":60,"inLanguage":22,"description":14,"dateModified":61,"datePublished":61,"encodingFormat":60,"isAccessibleForFree":62,"interactionStatistic":63},"DigitalDocument",{"name":9,"@type":56},"Person",{"url":40,"name":58,"@type":59},"DocShare","Organization","application/pdf","2026-08-05",true,{"@type":64,"interactionType":65,"userInteractionCount":4},"InteractionCounter",{"@type":66},"ViewAction",{"@type":68,"mainEntity":69},"FAQPage",[70,76,80],{"name":71,"@type":72,"acceptedAnswer":73},"Why is optimizing food bank locations important?","Question",{"text":74,"@type":75},"Food banks are vital for food-insecure families, but lack of transportation and available service locations limits access. Optimizing locations can improve coverage and reduce the distance between households and aid resources.","Answer",{"name":77,"@type":72,"acceptedAnswer":78},"What machine learning method does the paper use?",{"text":79,"@type":75},"The paper uses the K-means clustering algorithm. It leverages its speed and ability to process large datasets without requiring labeled training data.",{"name":81,"@type":72,"acceptedAnswer":82},"How does the approach handle income-related factors?",{"text":83,"@type":75},"A weighted K-means variant is applied when income data is available, aiming to prioritize lower-income households when generating candidate food bank locations.","https://schema.org",{"og:url":51,"og:type":86,"og:title":13,"og:site_name":58,"og:description":14},"article",{"robots":88,"canonical":51},"index,follow",{"doc_id":7,"site_id":23},{"code":4,"msg":5,"data":91},[92,96,100,104,109,114,119,122,126,129,133],{"id":20,"doc_module":4,"doc_module_name":45,"category_name":93,"show_sort_weight":94,"slug":95},"Story & Novel",90,"story-novel",{"id":46,"doc_module":4,"doc_module_name":45,"category_name":97,"show_sort_weight":98,"slug":99},"Literature",80,"literature",{"id":52,"doc_module":4,"doc_module_name":45,"category_name":101,"show_sort_weight":102,"slug":103},"Exam",70,"exam",{"id":105,"doc_module":4,"doc_module_name":45,"category_name":106,"show_sort_weight":107,"slug":108},5,"Comic",60,"comic",{"id":110,"doc_module":4,"doc_module_name":45,"category_name":111,"show_sort_weight":112,"slug":113},6,"Technology",50,"technology",{"id":115,"doc_module":4,"doc_module_name":45,"category_name":116,"show_sort_weight":117,"slug":118},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":45,"category_name":12,"show_sort_weight":120,"slug":121},30,"research-report",{"id":123,"doc_module":4,"doc_module_name":45,"category_name":124,"show_sort_weight":28,"slug":125},9,"Religion & Spirituality","religion-spirituality",{"id":28,"doc_module":4,"doc_module_name":45,"category_name":127,"show_sort_weight":28,"slug":128},"World Cup","world-cup",{"id":130,"doc_module":4,"doc_module_name":45,"category_name":131,"show_sort_weight":130,"slug":132},10,"Lifestyle","lifestyle",{"id":134,"doc_module":4,"doc_module_name":45,"category_name":135,"show_sort_weight":105,"slug":136},19,"General","general"]