Feasibility Model of Solar Energy Plants by ANN and MCDM Techniques

  • Mrinmoy Majumder
  • Apu K. Saha

Part of the SpringerBriefs in Energy book series (BRIEFSENERGY)

Table of contents

  1. Front Matter
    Pages i-x
  2. Mrinmoy Majumder, Apu K. Saha
    Pages 1-4
  3. Mrinmoy Majumder, Apu K. Saha
    Pages 5-8
  4. Mrinmoy Majumder, Apu K. Saha
    Pages 9-12
  5. Mrinmoy Majumder, Apu K. Saha
    Pages 13-16
  6. Mrinmoy Majumder, Apu K. Saha
    Pages 17-20
  7. Mrinmoy Majumder, Apu K. Saha
    Pages 21-45
  8. Mrinmoy Majumder, Apu K. Saha
    Pages 47-49

About this book

Introduction

This Brief highlights a novel model to find out the feasibility of any location to produce solar energy. The model utilizes the latest multi-criteria decision making techniques and artificial neural networks to predict the suitability of a location to maximize allocation of available energy for producing optimal amount of electricity which will satisfy the demand from the market. According to the results of the case studies further applications are encouraged.

Keywords

Analytical Hierarchy Process ELECTRE EVAMIX Fuzzy Logic Decision Making Multi Criteria Decision Making (MCDM) Network Topology Neural Networks Neuro-Genetic Model Solar Energy Plants

Authors and affiliations

  • Mrinmoy Majumder
    • 1
  • Apu K. Saha
    • 2
  1. 1.Department of Civil EngineeringNational Institute of TechnologyAgartalaIndia
  2. 2.Department of MathematicsNational Institute of TechnologyAgartalaIndia

Bibliographic information

  • DOI https://doi.org/10.1007/978-981-287-308-8
  • Copyright Information The Author(s) 2016
  • Publisher Name Springer, Singapore
  • eBook Packages Energy
  • Print ISBN 978-981-287-307-1
  • Online ISBN 978-981-287-308-8
  • Series Print ISSN 2191-5520
  • Series Online ISSN 2191-5539
  • About this book
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