Megha Rathi & Adwitiya Sinha 
Advanced Computational Techniques for Sustainable Computing [PDF ebook] 

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Advanced Computational Techniques for Sustainable Computing is considered multi-disciplinary field encompassing advanced computational techniques across several domain, including, Computer Science, Statistical Computation and Electronics Engineering. The core idea of sustainable computing is to deploy algorithms, models, policies and protocols to improve energy efficiency and management of resources, enhancing ecological balance, biological sustenance and other services on societal contexts.The book offers a comprehensive coverage of some of the most essential topics: It provides an insight on building smart sustainable solutions. Includes details of applying mining, learning, IOT and sensor-based techniques for sustainable computing. Entails data extraction from various sources followed with pre-processing of data, and how to make effective use of extracted data for application-based research. Involves practical usage of data analytic language, including R, Python, etc. for improving sustainable services offered by multi-disciplinary domains. Encompasses comparison and analysis of recent technologies and trends. Includes development of smart models for information gain and effective decision making with visualization. The readers would get acquainted with the utilization of massive data sets for intelligent mining and processing. It includes the integration of data mining techniques for effective decision-making in the social, economic, and global environmental domains to achieve sustainability. The implementation of computational frameworks can be accomplished using open-source software for the building of resource-efficient models. The content of the book demonstrates the usage of data science and the internet of things for the advent of smart and realistic solutions for attaining sustainability.

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语言 英语 ● 格式 PDF ● 网页 338 ● ISBN 9781000454314 ● 编辑 Megha Rathi & Adwitiya Sinha ● 出版者 CRC Press ● 发布时间 2022 ● 下载 3 时 ● 货币 EUR ● ID 8410592 ● 复制保护 Adobe DRM
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