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Titlebook: Innovations in Computer Science and Engineering; Proceedings of the T H. S. Saini,Rishi Sayal,Rajkumar Buyya Conference proceedings 2023 Th

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書目名稱Innovations in Computer Science and Engineering
副標(biāo)題Proceedings of the T
編輯H. S. Saini,Rishi Sayal,Rajkumar Buyya
視頻videohttp://file.papertrans.cn/468/467064/467064.mp4
概述Presents recent innovative research in the field of computational and artificial intelligence.Discusses the outcomes of ICICSE 2022, held in Hyderabad, India.Serves as a reference resource for researc
叢書名稱Lecture Notes in Networks and Systems
圖書封面Titlebook: Innovations in Computer Science and Engineering; Proceedings of the T H. S. Saini,Rishi Sayal,Rajkumar Buyya Conference proceedings 2023 Th
描述.This book features a collection of high-quality, peer-reviewed research papers presented at the 10th International Conference on Innovations in Computer Science & Engineering (ICICSE 2022), held at Guru Nanak Institutions, Hyderabad, India, on 16–17 September 2022. It covers the latest research in data science and analytics, cloud computing, machine learning, data mining, big data and analytics, information security and privacy, wireless and sensor networks and IoT applications, artificial intelligence, expert systems, natural language processing, image processing, computer vision, and artificial neural networks..
出版日期Conference proceedings 2023
關(guān)鍵詞Data Science and Analytics; Internet of Things; Cloud Computing; Artificial Intelligence; Wireless and S
版次1
doihttps://doi.org/10.1007/978-981-19-7455-7
isbn_softcover978-981-19-7454-0
isbn_ebook978-981-19-7455-7Series ISSN 2367-3370 Series E-ISSN 2367-3389
issn_series 2367-3370
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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V. Ramya,E. Vinay Kumar,G. S. Gopika,G. Manoj Mittelpunkt der - beit von Daniel B?llhoff. Ziel ist nicht der Merger, sondern vielmehr der, wenn man im gleichen Wortlaut bleiben will, ?Demerger“. Unternehme978-3-8349-0871-1978-3-8349-8297-1Series ISSN 2945-8439 Series E-ISSN 2945-8447
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Hybrid Power Generation Forecasting Using an Intellectual Evolutionary Energy-Preserve Rate Cluster assessment model is proposed, which has the advantage of estimating from real wind farms and statistical Weather Forecast (WF) data and has proven to be a nominal method for improving the predictive accuracy of Multi-term WPG. The primary step of the Energy-Preserve Rate Clustering (EPRC) method is
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