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Titlebook: Computational Intelligence and Sustainable Systems; Intelligence and Sus H. Anandakumar,R. Arulmurugan,Chow Chee Onn Book 2019 Springer Nat

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發(fā)表于 2025-3-21 18:38:22 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Computational Intelligence and Sustainable Systems
副標(biāo)題Intelligence and Sus
編輯H. Anandakumar,R. Arulmurugan,Chow Chee Onn
視頻videohttp://file.papertrans.cn/233/232443/232443.mp4
概述Presents the most recent challenges and developments in computational intelligence for sustainable systems and their best practices for application.Includes high quality research contributions from a
叢書名稱EAI/Springer Innovations in Communication and Computing
圖書封面Titlebook: Computational Intelligence and Sustainable Systems; Intelligence and Sus H. Anandakumar,R. Arulmurugan,Chow Chee Onn Book 2019 Springer Nat
描述.This book features research related to computational intelligence and energy and thermal aware management of computing resources. The authors publish original and timely research in current areas of power, energy, temperature, and environmental engineering as and advances in computational intelligence that are benefiting the fields. Topics include signal processing architectures, algorithms, and applications; biomedical informatics and computation; artificial intelligence and machine learning; green technologies in information; and more. The book includes contributions from a wide range of researchers, academicians, and industry professionals. The book is made up both of extended papers presented at the International Conference on Intelligent Computing and Sustainable System (ICICSS 2018), September 20-21, 2018, and other accepted papers on R&D and original research work related to the practice and theory of technologies to enable and support Intelligent Computing applications..
出版日期Book 2019
關(guān)鍵詞Computational intelligence in signal processing; Image Computing; Green technologies in AI and Machine
版次1
doihttps://doi.org/10.1007/978-3-030-02674-5
isbn_ebook978-3-030-02674-5Series ISSN 2522-8595 Series E-ISSN 2522-8609
issn_series 2522-8595
copyrightSpringer Nature Switzerland AG 2019
The information of publication is updating

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Strahlenbedingte Lebensverkürzung improves the validation set accuracy by a noticeable margin. This paper demonstrates the effectiveness of using the SAE model over DNN with the performance analysis of binary handwritten image with time and accuracy trade-off.
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Biologische Bedeutung der Umweltstrahlungen,ent and thus provides a whole new world of experience to demanding prospects, customers, and end users. This book chapter is aimed at discussing the potential applications, research trends, avenues, challenges, and future prospects of artificial intelligence and AR.
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,?Fühlen“ von und ?Reaktion“ auf Strahlung,xperience. The wireless BAN system assumes that the primary user’s signal does not change periodically until the channel is opportunistically used by a secondary user. To overcome the aforesaid problems of wireless body area networks, cognitive radio-enabled WBAN is devised by proposing an evolution
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Organdosen bei DSA-Untersuchungen,uated our methodology on real protein structure alignments and compared it with some of the well-known methods in the concerned area. The results which we gained after the experimental analysis clearly give the idea about the superiority of the presented method.
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Performance Analysis of Deep Neural Network and Stacked Autoencoder for Image Classification, improves the validation set accuracy by a noticeable margin. This paper demonstrates the effectiveness of using the SAE model over DNN with the performance analysis of binary handwritten image with time and accuracy trade-off.
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