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Metaheuristics for big data / Clarisse Dhaenens, Laetitia Jourdan.

By: Series: Computer engineering series. Metaheuristics set ; volume 5Publisher: London : London, UK ; Hoboken, NJ : John Wiley & Sons, Inc., 2016Description: 1 online resource (xvi, 188 pages)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781119347569
  • 1119347564
  • 1119347580
  • 9781119347583
  • 9781119347606
  • 1119347602
Subject(s): Genre/Form: Additional physical formats: Print version:: Metaheuristics for big data.DDC classification:
  • 519.6 23
LOC classification:
  • QA402.5 .C53 2016
Online resources:
Contents:
Optimization and Big Data -- Metaheuristics : A Short Introduction -- Metaheuristics and Parallel Optimization -- Metaheuristics and Clustering -- Metaheuristics and Association Rules -- Metaheuristics and (Supervised) Classification -- On the Use of Metaheuristics for Feature Selection in Classification -- Frameworks.
Summary: This book deals with the management and valuation of energy storage in electric power grids, highlighting the interest of storage systems in grid applications and developing management methodologies based on artificial intelligence tools. The authors highlight the importance of storing electrical energy, in the context of sustainable development, in'smart cities' and'smart transportation', and discuss multiple services that storing electrical energy can bring. Methodological tools are provided to build an energy management system storage following a generic approach. These tools are based on causal formalisms, artificial intelligence and explicit optimization techniques and are presented throughout the book in connection with concrete case studies.
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Optimization and Big Data -- Metaheuristics : A Short Introduction -- Metaheuristics and Parallel Optimization -- Metaheuristics and Clustering -- Metaheuristics and Association Rules -- Metaheuristics and (Supervised) Classification -- On the Use of Metaheuristics for Feature Selection in Classification -- Frameworks.

This book deals with the management and valuation of energy storage in electric power grids, highlighting the interest of storage systems in grid applications and developing management methodologies based on artificial intelligence tools. The authors highlight the importance of storing electrical energy, in the context of sustainable development, in'smart cities' and'smart transportation', and discuss multiple services that storing electrical energy can bring. Methodological tools are provided to build an energy management system storage following a generic approach. These tools are based on causal formalisms, artificial intelligence and explicit optimization techniques and are presented throughout the book in connection with concrete case studies.

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