[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-123917-en":3,"doc-seo-123917-105":30,"detail-sidebar-cat-0-en-105":91},{"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":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},123917,4398048950312,"Violet","https://ap-avatar.wpscdn.com/avatar/400002538284de19e3c?_k=1778320343897328908",8,"Research & Report","Investigating shared bike usage patterns in correlation with weather conditions through the application of machine learning algorithms","This Master’s Thesis analyzes shared bike usage in relation to weather conditions, using machine learning models to predict future demand from weather forecasts. As shared mobility grows in urban areas, dependable forecasting support is essential for improving system efficiency. The study applies supervised learning on a one-year dataset for Vicenza, linking bike rentals with corresponding meteorological variables. A random forest model yields the most accurate results among tested algorithms.","UNIVERSITY OFPADOVA  \nDEPARTMENT OF MANAGEMENT AND ENGINEERING DTG  \nMASTER’S THESIS IN MANAGEMENT ENGINEERING  \nInvestigating shared bike usage patterns in  \ncorrelation with weather conditions through  \nthe application of machine learning algorithms  \nSUPERVISOR MASTERCANDIDATE  \nPROF.SSAMARTA DISEGNA MARZIEH JAVANMARDI JALALABADI  \nCO-SUPERVISOR  \nElena Barzizza  \nSTUDENT ID  \n2043103  \nAcademic Year  \n2023-2024  \nMaster Thesis  \nMaster of science in Management Engineering  \nInvestigating shared bike usage patterns in correlation with weather conditions through the application of machine learning algorithms  \nAuthor:  \nMarzieh Javanmardi Jalalabadi  \nSupervisor:  \nMarta Disegna  \nTo my family  \nTo my friends  \nتقدیم به خانواده امتقدیم به دوستا یم  \nABSTRACT(EN)  \nThis Master's Thesis presents an analysis of shared bike usage based on weather conditions, utilizing machine learning algorithms capable of predicting future shared bike usage based on weather forecasts. As these services become increasingly integral to urban mobility, the reliability of supporting activities, such as accurate weather forecasts, is crucial to enhancing the overall efficiency of the system.  \nThe machine learning algorithms employed in this Thesis belong to the category of supervised learning techniques. These algorithms learn to predict the desired parameter by analyzing a vast dataset containing numerous historical examples. The dataset, in this case, spans one year of records detailing the number of bikes rented in Vicenza, along with the corresponding weather conditions during that period.  \nAmong the various algorithms explored, the random forest algorithm emerged as the most effective in providing accurate results.  \nThis study identifies an opportunity for the municipality to formulate targeted strategies promoting year-round bike usage based on weather-related patterns. The positive correlation between mean temperature, solar radiation, and extended trip durations in summer suggests a propensity for heightened bike activity during warmer and sunnier conditions. In light of these findings, initiatives such as promoting bike-sharing programs, improving bike-friendly infrastructure, and organizing events during the summer months are recommended to capitalize on this observed trend, fostering increased community engagement and sustainable transportation habits.  \nABSTRACT(IT)  \nQuesta tesi di laurea presenta un'analisi dell'utilizzo condiviso delle biciclette in base alle condizioni meteorologiche, utilizzando algoritmi di apprendimento automatico capaci di prevedere l'utilizzo futuro delle biciclette condivise in base alle previsioni meteorologiche. Poiché questi servizi diventano sempre più fondamentali per la mobilità urbana, la affidabilità delle attività di supporto, come le previsioni meteorologiche accurate, è cruciale per migliorare l'efficienza complessiva del sistema.  \nGli algoritmi di apprendimento automatico impiegati in questa tesi appartengono alla categoria delle tecniche di apprendimento supervisionato. Questi algoritmi imparano aprevedere il parametro desiderato analizzando un vasto set di dati contenente numerosiesempi storici. Il set di dati, in questo caso, copre un anno di registrazioni chedettagliano il numero di biciclette noleggiate a Vicenza, insieme alle condizioni meteorologiche corrispondenti durante quel periodo.  \nTra i vari algoritmi esplorati, l'algoritmo random forest è emerso come il più efficace nel fornire risultati accurati.  \nQuesto studio identifica un'opportunità per il comune di formulare strategie mirate a promuovere l'utilizzo delle biciclette durante tutto l'anno basandosi su modelli legati alle condizioni meteorologiche. La correlazione positiva tra temperatura media, radiazione solare e durata prolungata dei viaggi durante l'estate suggerisce una propensione per un'attività più intensa delle biciclette durante condizioni più calde esoleggiate. Alla luce di questi risultati, si raccomandano iniziati","cbCailR0AT8jrA3z","https://ap.wps.com/l/cbCailR0AT8jrA3z","pdf",3728206,1,102,"English","en",105,"# Abstract\n## Machine learning approach and dataset\n## Key findings and recommendations","[{\"question\":\"What is the main objective of the thesis?\",\"answer\":\"To analyze shared bike usage patterns and predict future bike demand based on weather forecasts using machine learning algorithms.\"},{\"question\":\"What type of machine learning techniques does the thesis use?\",\"answer\":\"It uses supervised learning techniques, training models on historical records to predict the target parameter.\"},{\"question\":\"Which algorithm performed best in the study?\",\"answer\":\"The random forest algorithm emerged as the most effective, providing the most accurate results.\"}]","Investigating shared bike usage patterns in correlation with weather conditions through the application of machine learning algorithms | PDF",1785819234,257,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"investigating-shared-bike-usage-patterns-in-correlation-with-weather-conditions-through-the-application-of-machine-learning-algorithms","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/investigating-shared-bike-usage-patterns-in-correlation-with-weather-conditions-through-the-application-of-machine-learning-algorithms/123917/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-04",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What is the main objective of the thesis?","Question",{"text":75,"@type":76},"To analyze shared bike usage patterns and predict future bike demand based on weather forecasts using machine learning algorithms.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What type of machine learning techniques does the thesis use?",{"text":80,"@type":76},"It uses supervised learning techniques, training models on historical records to predict the target parameter.",{"name":82,"@type":73,"acceptedAnswer":83},"Which algorithm performed best in the study?",{"text":84,"@type":76},"The random forest algorithm emerged as the most effective, providing the most accurate results.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]