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Titlebook: Artificial Intelligence: Theory and Applications; Proceedings of AITA Harish Sharma,Antorweep Chakravorty,Rajani Kumari Conference proceed

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發(fā)表于 2025-3-21 16:26:47 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱Artificial Intelligence: Theory and Applications
期刊簡(jiǎn)稱Proceedings of AITA
影響因子2023Harish Sharma,Antorweep Chakravorty,Rajani Kumari
視頻videohttp://file.papertrans.cn/163/162582/162582.mp4
發(fā)行地址Presents high-quality research in the areas of artificial intelligence and its applications.Features the outcomes of AITA 2023, held in Bengaluru, India.Serves as a reference resource for researchers
學(xué)科分類Lecture Notes in Networks and Systems
圖書封面Titlebook: Artificial Intelligence: Theory and Applications; Proceedings of AITA  Harish Sharma,Antorweep Chakravorty,Rajani Kumari Conference proceed
影響因子.This book features a collection of high-quality research papers presented at International Conference on Artificial Intelligence: Theory and Applications (AITA 2023), held during 11–12 August 2023 in Bengaluru, India. The book is divided into two volumes and presents original research and review papers related to artificial intelligence and its applications in various domains including health care, finance, transportation, education, and many more..
Pindex Conference proceedings 2024
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https://doi.org/10.1007/978-3-642-12898-1d (GICS). A range of liquidity and financial variables, including net working capital, quick ratio, debt–equity ratio, and financial autonomy rate, are used in the study to assess the company‘s performance across various industries. The study uses trend analysis and panel regression techniques to in
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Bernhard Badura,Helmut Schr?der,Katrin Macco health. Newly, artificial intelligence (AI) technologies have been created to aid mental health practitioners, such as psychiatrists and psychologists, in decision-making based on the historic data of patients (for example, medical records, behavioral data, social media use, etc.). These AI methods
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https://doi.org/10.1007/978-3-642-21655-8set, there could be problems with the accuracy of the information obtained. Morphological segmentation processes have progressed quickly as a consequence of the massive increase in digital resources. It may be difficult to distinguish between the quality of the questions and all of their substance o
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https://doi.org/10.1007/978-3-642-21655-8ironment. To make informed decisions, decision-makers often rely on robust and efficient methods that consider multiple criteria simultaneously. In this regard, this paper presents a novel approach that combines the Dempster–Shafer theory and the Maximum Entropy Principle to address the supplier sel
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