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4.5 MB
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8F2A39D85CD7CC4F6B3981B167A4541030C1A4B8
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Added:
July 10, 2025, 5:29 p.m.
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(Last updated: July 10, 2025, 5:30 p.m.)
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| ['Kulkarni S. Artificial Intelligence-driven Models..Environmental Management 2025.pdf'] | 0 bytes |
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| Uploaded by indexFroggy | Size 16.5 MB | Health [ 21 /9 ] | Added 2023-07-01 |
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SOURCE: Kulkarni S. Artificial Intelligence-driven Models..Environmental Management 2025
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COVER

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MEDIAINFO
Textbook in PDF format Step-by-step guidelines for the development of Artificial Neural Network-based environmental pollution models. Artificial Intelligence-Driven Models for Environmental Management delves into the application of AI across a plethora of areas in environmental management, including climate forecasting, natural resource optimization, waste management, and biodiversity conservation. This book shows how AI can help in monitoring, predicting, and mitigating environmental impacts with tremendous accuracy and speed by leveraging machine learning, deep learning, and other data-driven models. The methodologies explored in this volume reflect a synthesis of Computational Intelligence, Data Science, and ecological expertise, underscoring how AI-driven systems have been making strides in managing and preserving our planet’s natural resources. The text is structured to guide readers through numerous AI models and their practical environmental management applications, showcasing theoretical foundations as well as case studies. This book also addresses the challenges and ethical considerations related to deploying AI in ecological contexts, underscoring the importance of transparency, inclusivity, and alignment with sustainability goals. Sample topics discussed in Artificial Intelligence-Driven Models for Environmental Management include Tools and methods for monitoring and predicting environmental pollutants faster and more accurately AI technology for the protection of water supplies from contamination to produce healthier foods Use of AI for the evaluation of the impacts of environmental pollution on human health AI and waste management technologies for sustainable agriculture and soil management The role of AI in environmental research and sustainability and key social and economic aspects of natural resource management through AI Artificial Intelligence-Driven Models for Environmental Management is a timely, forward-thinking resource for a diverse readership, including researchers, policymakers, environmental scientists, and AI practitioners. Preface Part I Foundations of AI in Environmental Management Application of AI in Environmental Sustainability The Role of AI in Environmental Research and Sustainability AI and Environmental Data Science Part II AI in Natural Resource Management Application of AI for Natural Source Management Future Prospects of AI for Management of Natural Resources Part III AI Models for Climate Change Mitigation and Adaptation AI-Driven Environmental Real-Time Monitoring, and Screening AI-Driven Environmental Problem Design for Sustainable Solutions AI in Soil Health Management for Health Food Production Part IV AI in Pollution Control and Waste Management AI for Evaluation of the Impacts of Environmental Pollution on Human Health Artificial Intelligence for Air/Water Quality Prediction AI Technology for Protection of Water Supplies from Contamination to Produce Healthy Foods AI in Waste Management Technologies for Sustainable Agriculture The Internet of Things (IoTs) for Environmental Pollution
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