Feasibility model of solar energy plants by ANN and MCDM techniques /

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Bibliographic Details
Author / Creator:	Majumder, Mrinmoy, author.
Imprint:	Singapore : Springer, 2016.
Description:	1 online resource (x, 49 pages) : illustrations (some color)
Language:	English
Series:	SpringerBriefs in energy, 2191-5520 SpringerBriefs in energy,
Subject:	Solar energy -- Computer simulation. Solar energy -- Decision making. Solar energy -- Computer simulation. Solar energy -- Decision making.
Format:	E-Resource Book
URL for this record:	http://pi.lib.uchicago.edu/1001/cat/bib/11255348

Hidden Bibliographic Details
Other authors / contributors:	Saha, Apu K., author.
ISBN:	9789812873088 9812873082 9812873074 9789812873071 9789812873071
Digital file characteristics:	text file PDF
Notes:	Includes bibliographical references. English. Online resource; title from PDF title page (SpringerLink, viewed May 4, 2016).
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.
Other form:	Printed edition: 9789812873071
Standard no.:	10.1007/978-981-287-308-8 10.1007/978-981-287-

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