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Intelligent Decision Support Systems for Sustainable Computing : Paradigms and Applications / edited by Arun Kumar Sangaiah, Ajith Abraham, Patrick Siarry, Michael Sheng

Contributor(s): Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Studies in Computational Intelligence ; 705 | SpringerLink Bücher | Springer eBook Collection EngineeringPublisher: Cham : Springer, 2017Description: Online-Ressource (XVI, 289 p. 108 illus., 86 illus. in color, online resource)ISBN:
  • 9783319531533
Subject(s): Additional physical formats: 9783319531526 | Erscheint auch als: 978-3-319-53152-6 Druck-Ausgabe | Printed edition: 9783319531526 DDC classification:
  • 006.3
LOC classification:
  • Q342
DOI: DOI: 10.1007/978-3-319-53153-3Online resources: Summary: 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 areaSummary: Intelligent Decision Support Systems for Sustainable Computing -- A Genetic Algorithm based Efficient Load Distribution Strategy for Handling Large Scale Workloads on Sustainable Computing Systems -- Efficiency in Energy Decision Support Systems using Soft Computing Techniques -- Computational Intelligence Based Heuristic Approach for Maximizing Energy Efficiency in Internet of Things -- Distributed Algorithm with Inherent Intelligence for Multi-Cloud Resource Provisioning -- Parameter Optimization methods based on Computational Intelligence Techniques in Context of Sustainable Computing -- The Maximum Power Point tracking using Fuzzy Logic Algorithm for DC Motor based Conveyor System -- Differential Evolution Based Significant Data Region Identification on Large Storage Drives -- A Fuzzy Based Power Switching Selection for Residential Application to beat Peak Time Power Demand -- Energy Saving Using Memorization: A Novel Energy-Efficient and Fault Tolerant Algorithm -- Analyzing Slavic Textual Sentiment using Deep Convolutional Neural Networks -- Intelligent Decision Support System for an Integrated Pest Management in Apple Orchard -- Analysis of Error Propagation in Safety Critical Software Systems: An Approach based on UGF -- A Framework for Analyzing Uncertainty in Data using Computational Intelligence Techniques --PPN: PPN: 1657558037Package identifier: Produktsigel: ZDB-2-ENG
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