[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-119957-en":3,"doc-seo-119957-105":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":20,"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},119957,4398048949847,"Eliana","https://ap-avatar.wpscdn.com/avatar/400002536579ef2da7f?_k=1778318612642679267",8,"Research & Report","Simulation and Assessment of Bitcoin Prediction Using Machine Learning Methodology","Bitcoin price forecasting faces volatility, multi-factor drivers, and limited history, making robust models difficult. This study explores how improved data analysis and advanced machine learning can address limitations of traditional time-series, statistical, and econometric approaches. By combining historical price data with fundamental indicators and market sentiment analysis, the methodology aims to enhance prediction accuracy. Results compare multiple algorithms and assess their ability to capture underlying Bitcoin price dynamics, supporting use in risk management, portfolio optimization, and trading strategies.","Simulation and Assessment of Bitcoin Prediction Using Machine Learning Methodology  \nAshish Kumar Singh1, Dr. Mukesh Kumar2  \n1Research Scholar, Department ofCSE, Rabindra Nath Tagore University, Bhopal, India 2Associate Professor, Department of CSE, Rabindra Nath Tagore University, Bhopal, India  \nAbstract—: The market for digital currencies is rapidly growing, attracting traders, investors, and businesspeople on a worldwide scale that hasn't been witnessed in this century. By providing comparison studies and insights from the price data of crypto currency marketplaces, it will help in recording the behaviour and habits of such a lucratively demanding and rapidly expanding business. The bitcoin market is reaching one of its peak levels ever in 2021. The emergence of new exchanges has made cryptocurrencies more approachable to the general public, hence boosting their attractiveness. This has increased the number of users and interest in cryptocurrencies, along with a number of reliable crypto ventures started by some of the founders. Virtual currencies are growing more and more well-liked, and businesses like Tesla, Dell, and Microsoft are now embracing them. Decentralized digital currencies are becoming more and more popular, thus it's more crucial than ever to properly inform the public about the new currencies as they proliferate so that people are aware of what they possess and how their money is being invested.  \nAnalysis shows that soft computing and machine learning techniques can anticipate more accurately than any other technique now available to researchers. Finally, it is claimed that ANN, SVMs, and other similar machine learning techniques are useful for predicting global stock market fluctuations..  \nKeywords-Bitcoin Forecasting, Machine Learning, Regression, Artificial Neural Network, Back-propagation, Forecasting, Stock market, Feed forward, RMSE  \nI. INTRODUCTION  \nBitcoin, introduced by Satoshi Nakamoto in 2009, has emerged asthe pioneer of blockchain-based cryptocurrencies. Its decentralized nature and potential to operate outside the control of traditional financial institutions have garnered widespread interest and investment. As a result, Bitcoin's value has exhibited significant volatility, making it a highly attractive yet risky investment option. Investors, traders, and financial analysts are constantly seeking reliable methods to forecast Bitcoin's value to make informed decisions.  \nThe value forecasting of Bitcoin poses several challenges due to its unique characteristics. Unlike traditional financial assets, Bitcoin's value is influenced by a wide range of factors, including market sentiment, technological developments, regulatory changes, macroeconomic events, and the adoption rate of cryptocurrencies. Additionally, the absence of a central governing authority and the relatively short history of Bitcoin make it challenging to establish robust forecasting models.  \nPrevious research on Bitcoin value forecasting has predominantly utilized traditional time-series analysis, statistical models, and econometric approaches. However, these methods often fall short in capturing the complex dynamics of the cryptocurrency market, resulting in limited accuracy and predictive power.  \nThis research aims to address the limitations of existing forecasting methodologies by incorporating improved data analysis and advanced machine learning techniques. The proposed approach combines historical price data with fundamental indicators and market sentiment analysis to enhance the accuracy of predictions. We hypothesize that the inclusion of sentiment analysis will provide valuable insights  \ninto the impact of market sentiment on Bitcoin's value and improve the overall forecasting performance.  \nIn this paper, we present a detailed analysis of the proposed methodology and evaluate its effectiveness through sample results. We compare the performance of various machine learning algorithms and demonstrate their capability ","cbCaia93s7jnSjRj","https://ap.wps.com/l/cbCaia93s7jnSjRj","pdf",209190,1,5,"English","en",105,"# Introduction\n## Motivation and challenges\n## Research objective and proposed approach\n# Related Works\n## Time-series and statistical models\n## Machine learning approaches\n## Research gaps","[{\"question\":\"Why is Bitcoin value forecasting particularly challenging?\",\"answer\":\"Bitcoin’s value is influenced by market sentiment, technological developments, regulatory changes, macroeconomic events, and adoption rates. Its decentralized nature and short history also make establishing robust forecasting models difficult.\"},{\"question\":\"What does the proposed methodology combine to improve prediction accuracy?\",\"answer\":\"It combines historical price data with fundamental indicators and market sentiment analysis to better reflect how sentiment impacts Bitcoin’s value and improve overall forecasting performance.\"},{\"question\":\"Which categories of algorithms are compared in the study?\",\"answer\":\"The paper compares multiple machine learning algorithms and evaluates their effectiveness in capturing underlying patterns in Bitcoin’s price movements, including approaches such as ANN and SVM-based methods.\"}]","Simulation and Assessment of Bitcoin Prediction Using Machine Learning Methodology | PDF",1785727191,13,{"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},"simulation-and-assessment-of-bitcoin-prediction-using-machine-learning-methodology","",{"@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/simulation-and-assessment-of-bitcoin-prediction-using-machine-learning-methodology/119957/",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","2026-08-03",true,{"@type":65,"interactionType":66,"userInteractionCount":20},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"Why is Bitcoin value forecasting particularly challenging?","Question",{"text":75,"@type":76},"Bitcoin’s value is influenced by market sentiment, technological developments, regulatory changes, macroeconomic events, and adoption rates. Its decentralized nature and short history also make establishing robust forecasting models difficult.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What does the proposed methodology combine to improve prediction accuracy?",{"text":80,"@type":76},"It combines historical price data with fundamental indicators and market sentiment analysis to better reflect how sentiment impacts Bitcoin’s value and improve overall forecasting performance.",{"name":82,"@type":73,"acceptedAnswer":83},"Which categories of algorithms are compared in the study?",{"text":84,"@type":76},"The paper compares multiple machine learning algorithms and evaluates their effectiveness in capturing underlying patterns in Bitcoin’s price movements, including approaches such as ANN and SVM-based methods.","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},[93,97,101,105,109,114,119,122,127,130,134],{"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":21,"doc_module":4,"doc_module_name":46,"category_name":106,"show_sort_weight":107,"slug":108},"Comic",60,"comic",{"id":110,"doc_module":4,"doc_module_name":46,"category_name":111,"show_sort_weight":112,"slug":113},6,"Technology",50,"technology",{"id":115,"doc_module":4,"doc_module_name":46,"category_name":116,"show_sort_weight":117,"slug":118},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":120,"slug":121},30,"research-report",{"id":123,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":125,"slug":126},9,"Religion & Spirituality",20,"religion-spirituality",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":125,"slug":129},"World Cup","world-cup",{"id":131,"doc_module":4,"doc_module_name":46,"category_name":132,"show_sort_weight":131,"slug":133},10,"Lifestyle","lifestyle",{"id":135,"doc_module":4,"doc_module_name":46,"category_name":136,"show_sort_weight":21,"slug":137},19,"General","general"]