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Titlebook: Proceedings of International Conference on Recent Innovations in Computing; ICRIC 2023, Volume 2 Zoltán Illés,Chaman Verma,Pradeep Kumar Si

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發(fā)表于 2025-3-21 16:52:59 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Proceedings of International Conference on Recent Innovations in Computing
副標題ICRIC 2023, Volume 2
編輯Zoltán Illés,Chaman Verma,Pradeep Kumar Singh
視頻videohttp://file.papertrans.cn/765/764515/764515.mp4
概述Presents research works in innovations in computing.Discusses results of ICRIC 2023 held in Jammu, India.Serves as a reference for researchers and practitioners in academia and industry
叢書名稱Lecture Notes in Electrical Engineering
圖書封面Titlebook: Proceedings of International Conference on Recent Innovations in Computing; ICRIC 2023, Volume 2 Zoltán Illés,Chaman Verma,Pradeep Kumar Si
描述.This book features selected papers presented at the 6th International Conference on Recent Innovations in Computing (ICRIC 2023), held on 26–27 October 2023 at the Central University of Jammu, India, and organized by the university’s Department of Computer Science and Information Technology. The book is divided into two volumes, and it includes the latest research in the areas of software engineering, cloud computing, computer networks and Internet technologies, artificial intelligence, information security, database and distributed computing, and digital India..
出版日期Conference proceedings 2024
關鍵詞Internet of Things; Machine Learning; Deep Learning; Big Data Analytics; Robotics Cloud Computing; Comput
版次1
doihttps://doi.org/10.1007/978-981-97-3442-9
isbn_softcover978-981-97-3444-3
isbn_ebook978-981-97-3442-9Series ISSN 1876-1100 Series E-ISSN 1876-1119
issn_series 1876-1100
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
The information of publication is updating

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Proceedings of International Conference on Recent Innovations in Computing978-981-97-3442-9Series ISSN 1876-1100 Series E-ISSN 1876-1119
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https://doi.org/10.1007/978-981-97-3442-9Internet of Things; Machine Learning; Deep Learning; Big Data Analytics; Robotics Cloud Computing; Comput
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Zoltán Illés,Chaman Verma,Pradeep Kumar SinghPresents research works in innovations in computing.Discusses results of ICRIC 2023 held in Jammu, India.Serves as a reference for researchers and practitioners in academia and industry
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Anomaly Detection in Power Consumption: A Comprehensive Multi-technique Approachanomaly detection models. The LSTM autoencoder achieves balanced precision, recall, and high accuracy. These results emphasize the potential of the LSTM autoencoder as an effective approach for detecting anomalies in power consumption time series data, contributing to enhanced energy management practices.
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