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Titlebook: Intelligent Distributed Computing XIV; David Camacho,Domenico Rosaci,Mario Versaci Conference proceedings 2022 The Editor(s) (if applicabl

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书目名称Intelligent Distributed Computing XIV
编辑David Camacho,Domenico Rosaci,Mario Versaci
视频video
概述Presents recent research on intelligent distributed computing.Includes the scientific outcome of the 14th International Symposium on Intelligent Distributed Computing (IDC 2021).Written by leading exp
丛书名称Studies in Computational Intelligence
图书封面Titlebook: Intelligent Distributed Computing XIV;  David Camacho,Domenico Rosaci,Mario Versaci Conference proceedings 2022 The Editor(s) (if applicabl
描述.This book collects 43 regular papers received from 18 countries that present innovative advances in intelligent and distributed computing, encompassing both architectural and algorithmic results related to these fields. Significant attention is given to new models, techniques, and applications for distributed intelligent architectures and high-performance architectures, machine learning techniques, Internet of Things, blockchain, intelligent transport systems, data analytics, trust and reputation systems, and many others. The book includes the peer-reviewed proceedings of the 14th International Symposium on Intelligent Distributed Computing (IDC 2021), which was held in online mode due to the COVSARS2 pandemic situation, during September 16–18, 2021. . .The IDC 2021 event included sessions on Internet of Things, data analytics, machine learning, multi-agent systems, algorithms, future intelligent transport solutions, blockchain, intelligent distributed computing for cyber-physical security, and security and trust and reputation in intelligent environments..
出版日期Conference proceedings 2022
关键词Intelligent Distributed Computing; Computational Intelligence; Internet of Things; Blockchain; Intellige
版次1
doihttps://doi.org/10.1007/978-3-030-96627-0
isbn_softcover978-3-030-96967-7
isbn_ebook978-3-030-96627-0Series ISSN 1860-949X Series E-ISSN 1860-9503
issn_series 1860-949X
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
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Critical Comparison of Data Imputation Techniques at IoT Edgee. This work investigates how well-established techniques can be used for the imputation of contaminated data. We look at the performance of four algorithms for different contamination rates and error bursts of variable length. Furthermore, the algorithms are also evaluated on a constrained environm
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