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Feasibility model of solar energy plants by ANN and MCDM techniques [electronic resource] / Mrinmoy Majumder, Apu K. Saha.

Majumder, Mrinmoy, author.; Saha, Apu K. author.
2016
TJ810
Available Online
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Title
Feasibility model of solar energy plants by ANN and MCDM techniques [electronic resource] / Mrinmoy Majumder, Apu K. Saha.
Author
Majumder, Mrinmoy, author.
ISBN
9789812873088 (electronic book)
9812873082 (electronic book)
9789812873071
DOI
https://doi.org/10.1007/978-981-287-308-8
Published
Singapore : Springer, 2016.
Language
English
Description
1 online resource (x, 49 pages) : illustrations.
Item Number
10.1007/978-981-287-308-8 doi
Call Number
TJ810
Dewey Decimal Classification
621.47/1
Summary
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.
Bibliography, etc. Note
Includes bibliographical references.
Access Note
Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed May 4, 2016).
Added Author
Saha, Apu K. author.
Series
SpringerBriefs in energy.
Available in Other Form
Print version: 9789812873071
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Introduction
Justification
Solar Energy
Solar Energy
Importance
Benefits of Solar energy
MCDM
Definitions
Applications
Artificial Neural Network
Definition
Development Procedure of Models
Development of the Feasibility Model
Application of MCDM
Development of Feasibility Index
Model Validation of the Model
Sensitivity Analysis
Case Studies
Locations
Why this location ?
Results and Discussion
MCDM Results
ANN Results
Conclusion.

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