Intelligent Decision Support Systems for Sustainable Computing

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  • Intelligent Decision Support Systems for Sustainable Computing Book Detail

  • Author : Arun Kumar Sangaiah
  • Release Date : 2017-03-14
  • Publisher : Springer
  • Genre : Technology & Engineering
  • Pages : 296
  • ISBN 13 : 3319531530
  • File Size : 64,64 MB

Intelligent Decision Support Systems for Sustainable Computing by Arun Kumar Sangaiah PDF Summary

Book Description: This unique book dicusses the latest research, innovative ideas, challenges and computational intelligence (CI) solutions in sustainable computing. It presents novel, in-depth fundamental research on achieving a sustainable lifestyle for society, either from a methodological or from an application perspective. Sustainable computing has expanded to become a significant research area covering the fields of computer science and engineering, electrical engineering and other engineering disciplines, and there has been an increase in the amount of literature on aspects sustainable computing such as energy efficiency and natural resources conservation that emphasizes the role of ICT (information and communications technology) in achieving system design and operation objectives. The energy impact/design of more efficient IT infrastructures is a key challenge in realizing new computing paradigms. The book explores the uses of computational intelligence (CI) techniques for intelligent decision support that can be exploited to create effectual computing systems, and addresses sustainability problems in computing and information processing environments and technologies at the different levels of CI paradigms. An excellent guide to surveying the state of the art in computational intelligence applied to challenging real-world problems in sustainable computing, it is intended for scientists, practitioners, researchers and academicians dealing with the new challenges and advances in area.

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Intelligent Decision Support Systems

Intelligent Decision Support Systems

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This book, with invaluable contributions of Professor Franz Wotawa in chapters 5 and 7, presents the potential use and implementation of intelligent techniques

Intelligent Decision Support Systems

Intelligent Decision Support Systems

File Size : 33,33 MB
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Intelligent prediction and decision support systems are based on signal processing, computer vision (CV), machine learning (ML), software engineering (SE), know