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Titlebook: Artificial Intelligence and Environmental Sustainability; Challenges and Solut Hui Lin Ong,Ruey-an Doong,Atulya K. Nagar Book 2022 The Edit

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發(fā)表于 2025-3-21 19:26:11 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱(chēng)Artificial Intelligence and Environmental Sustainability
期刊簡(jiǎn)稱(chēng)Challenges and Solut
影響因子2023Hui Lin Ong,Ruey-an Doong,Atulya K. Nagar
視頻videohttp://file.papertrans.cn/163/162198/162198.mp4
發(fā)行地址Discusses comprehensive and cutting-edge research and development in implementation of AI.Explores the future research directions in the era of Industry 4.0.Covers technological and application aspect
學(xué)科分類(lèi)Algorithms for Intelligent Systems
圖書(shū)封面Titlebook: Artificial Intelligence and Environmental Sustainability; Challenges and Solut Hui Lin Ong,Ruey-an Doong,Atulya K. Nagar Book 2022 The Edit
影響因子.The book discusses comprehensive and cutting-edge research and development endeavors, as well as innovative solutions, in implementing AI and related technologies to meet and undertake current and future challenges towards ensuring environmental sustainability. It explores the future research directions in the era of Industry 4.0. In the beginning, an overview of the utilization of Al for environmental sustainability is provided. The remaining chapters of the book cover the technological and application aspects of Al for environmental sustainability with illustrative examples. Finally, challenges with respect to deploying Al to solving environmental problems and the future trends are covered..
Pindex Book 2022
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書(shū)目名稱(chēng)Artificial Intelligence and Environmental Sustainability影響因子(影響力)




書(shū)目名稱(chēng)Artificial Intelligence and Environmental Sustainability影響因子(影響力)學(xué)科排名




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Oluwayemi-Oniya Aderibigbe,Trynos Gumbo quality in near real time aiding faster decision-making and resulting in mitigation actions. The exponential digital transformations in every sector have led to platform technologies and in this chapter, we explore the network approaches platform ecosystems to adopt as opposed to a linear approach
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Lecture Notes in Networks and Systemsons. However, not all AI-based techniques are capable of real-time modelling. Therefore, this study is focussed on reviewing the AI-based techniques for real-time R-R modelling and discussing their capabilities, limitations, and potential areas for improvement. Finally, the potential future research
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Lecture Notes in Networks and Systems pharmaceutical tablets as functions of product formulation. The resulting rule-based model provides useful insights on how levels of additives can be optimized to give a product that performs well in the tableting process.
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https://doi.org/10.1007/978-981-97-3991-2untry-level economies. The proposed hybrid approach is capable of mapping an initial causal network using DEMATEL and then training the network through FCM. The network attained an accuracy of 73.20% on training and 73.81% on testing, revealing economic attractiveness and consumer demand as signific
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Lecture Notes in Networks and Systems first period (past 1999–2003) and 83.07% for the second period (2014–2017), respectively. Maps further highlighted changes in LULC classes over time. The LULC classes had changed substantially due to natural processes and anthropogenic actions. The study demonstrated the potential use of remap to m
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Artificial Intelligence and Environmental SustainabilityChallenges and Solut
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AI and Environmental Health: A Platform Ecosystem Perspective, quality in near real time aiding faster decision-making and resulting in mitigation actions. The exponential digital transformations in every sector have led to platform technologies and in this chapter, we explore the network approaches platform ecosystems to adopt as opposed to a linear approach
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