相關主題
商品描述
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.
商品描述(中文翻譯)
基於人工神經網路的環境污染模型開發的逐步指導
人工智慧驅動的環境管理模型 深入探討了人工智慧在環境管理各個領域的應用，包括氣候預測、自然資源優化、廢物管理和生物多樣性保護。本書展示了如何利用機器學習、深度學習及其他數據驅動模型，幫助監測、預測和減輕環境影響，並以極高的準確性和速度進行操作。本書中探討的方法論反映了計算智能、數據科學和生態專業知識的綜合，強調了人工智慧驅動系統在管理和保護我們地球自然資源方面所取得的進展。
文本結構旨在引導讀者了解多種人工智慧模型及其在環境管理中的實際應用，展示理論基礎以及案例研究。本書還探討了在生態環境中部署人工智慧所面臨的挑戰和倫理考量，強調透明度、包容性和與可持續發展目標的一致性的重要性。
在人工智慧驅動的環境管理模型中討論的示例主題包括：
- 更快、更準確地監測和預測環境污染物的工具和方法
- 保護水源免受污染的人工智慧技術，以生產更健康的食品
- 利用人工智慧評估環境污染對人類健康的影響
- 人工智慧和廢物管理技術在可持續農業和土壤管理中的應用
- 人工智慧在環境研究和可持續性中的角色，以及通過人工智慧管理自然資源的關鍵社會和經濟方面
人工智慧驅動的環境管理模型 是一本及時且具前瞻性的資源，適合包括研究人員、政策制定者、環境科學家和人工智慧從業者在內的多元讀者群。
作者簡介
Shrikaant Kulkarni, Ph.D., is an Adjunct Professor at Faculty of Business, Vicorian Institute of Technology, Melbourne, Australia. Dr. Kulkarni has been a senior academician and researcher for more than four decades. He has published over 100 research papers, 75+ book chapters, and edited 30+ reference books. He has expertise in the fields of materials science, green chemistry and engineering, and analytical chemistry, and Artificial Intelligence.
作者簡介(中文翻譯)
Shrikaant Kulkarni 博士是澳洲墨爾本維多利亞科技學院商學院的兼任教授。Kulkarni 博士在學術界和研究領域已有超過四十年的經驗。他已發表超過 100 篇研究論文、75 篇以上的書籍章節，並編輯了 30 本以上的參考書籍。他在材料科學、綠色化學與工程、分析化學以及人工智慧等領域具有專業知識。
