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Titlebook: Accelerating Discoveries in Data Science and Artificial Intelligence I; ICDSAI 2023, LIET Vi Frank M. Lin,Ashokkumar Patel,Bosubabu Sambana

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發(fā)表于 2025-3-21 19:01:32 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱(chēng)Accelerating Discoveries in Data Science and Artificial Intelligence I
期刊簡(jiǎn)稱(chēng)ICDSAI 2023, LIET Vi
影響因子2023Frank M. Lin,Ashokkumar Patel,Bosubabu Sambana
視頻videohttp://file.papertrans.cn/144/143641/143641.mp4
發(fā)行地址Discusses mathematically deep enough algorithms of data science to solve the real world problems.Explains the students AI techniques for several aspects of programming, sorting, pattern matching etc.A
學(xué)科分類(lèi)Springer Proceedings in Mathematics & Statistics
圖書(shū)封面Titlebook: Accelerating Discoveries in Data Science and Artificial Intelligence I; ICDSAI 2023, LIET Vi Frank M. Lin,Ashokkumar Patel,Bosubabu Sambana
影響因子.The Volume 1 book on Accelerating Discoveries in Data Science and Artificial Intelligence (Proceedings of ICDSAI 2023), that was held on April 24-25, 2023 by CSUSB USA, the International Association of Academicians (IAASSE), and the Lendi Institute of Engineering and Technology, Vizianagaram, India is intended to be used as a reference book for researchers and practitioners in the disciplines of AI and data science. The book introduces key topics and algorithms and explains how these contribute to healthcare, manufacturing, law, finance, retail, real estate, accounting, digital marketing, and various other fields. The book is primarily meant for academics, researchers, and engineers who want to employ data science techniques and AI applications to address real-world issues. Besides that, businesses and technology creators will also find it appealing to use in industry..
Pindex Conference proceedings 2024
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https://doi.org/10.1007/978-3-030-77896-5 necessity designing cycle. The list suggests a moderate improvement for aiding exercises in necessity designing in a global programming advancement worldview. This work is very beneficial for those with less experience working in global programming advancement.
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https://doi.org/10.1007/978-3-642-97696-4ID and WOA-PIDA control schemes were matched with recently developed nature-inspired computations. In addition to LPBO-PIPD, AOA-PIPD, and MPSO-PIPD, the suggested control schemes WOA-2DOFPID and WOA-PIDA are clearly more reliable, as evidenced by the comparison of the controllers.
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https://doi.org/10.1007/978-3-662-00578-1 that the determination coefficient R has a value close to 1 and the mean square error tends to 0. This confirms the average prediction of the model. For better performance, it is preferable to input more historical data and to combine ANNs with metaheuristic algorithms.
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