| 書目名稱 | Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making | | 副標(biāo)題 | Proceedings of the I | | 編輯 | Cengiz Kahraman,Selcuk Cebi,Irem Ucal Sari | | 視頻video | http://file.papertrans.cn/471/470214/470214.mp4 | | 概述 | Presents recent research on intelligent and fuzzy techniques in big data analytics and decision-making big data analytics.Includes the proceedings of the Intelligent and Fuzzy Techniques INFUS 2019 Co | | 叢書名稱 | Advances in Intelligent Systems and Computing | | 圖書封面 |  | | 描述 | .This book includes the proceedings of the Intelligent and Fuzzy Techniques INFUS 2019 Conference, held in Istanbul, Turkey, on July 23–25, 2019. Big data analytics refers to the strategy of analyzing large volumes of data, or big data, gathered from a wide variety of sources, including social networks, videos, digital images, sensors, and sales transaction records. Big data analytics allows data scientists and various other users to evaluate large volumes of transaction data and other data sources that traditional business systems would be unable to tackle. Data-driven and knowledge-driven approaches and techniques have been widely used in intelligent decision-making, and they are increasingly attracting attention due to their importance and effectiveness in addressing uncertainty and incompleteness. INFUS 2019 focused on intelligent and fuzzy systems with applications in big data analytics and decision-making, providing an international forum that brought together those actively involved in areas of interest to data science and knowledge engineering. These proceeding feature about 150 peer-reviewed papers from countries such as China, Iran, Turkey, Malaysia, India, USA, Spain, Fr | | 出版日期 | Conference proceedings 2020 | | 關(guān)鍵詞 | Intelligent Techniques; Fuzzy Techniques; Big Data Analytics; Decision Making; INFUS 2019; energy securit | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-030-23756-1 | | isbn_softcover | 978-3-030-23755-4 | | isbn_ebook | 978-3-030-23756-1Series ISSN 2194-5357 Series E-ISSN 2194-5365 | | issn_series | 2194-5357 | | copyright | Springer Nature Switzerland AG 2020 |
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