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切換: 標籤 | MARC模式 | ISBD

Feasibility model of solar energy pl...

Majumder, Mrinmoy.

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Feasibility model of solar energy plants by ANN and MCDM techniques

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Feasibility model of solar energy plants by ANN and MCDM techniques/ by Mrinmoy Majumder, Apu K. Saha.
作者:	Majumder, Mrinmoy.
其他作者:	Saha, Apu K.
出版者:	Singapore :Springer Singapore : : 2016.,
面頁冊數:	x, 49 p. :ill. (some col.), digital ;24 cm.
內容註:	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.
Contained By:	Springer eBooks
標題:	Solar energy - Computer simulation. -
電子資源:	http://dx.doi.org/10.1007/978-981-287-308-8
ISBN:	9789812873088

Feasibility model of solar energy plants by ANN and MCDM techniques
Majumder, Mrinmoy.

Feasibility model of solar energy plants by ANN and MCDM techniques[electronic resource] /by Mrinmoy Majumder, Apu K. Saha. - Singapore :Springer Singapore :2016. - x, 49 p. :ill. (some col.), digital ;24 cm. - SpringerBriefs in energy,2191-5520. - SpringerBriefs in energy..

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.

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.

ISBN: 9789812873088

Standard No.: 10.1007/978-981-287-308-8doiSubjects--Topical Terms:

2191478
Solar energy
--Computer simulation.

LC Class. No.: TJ810

Dewey Class. No.: 621.471

Feasibility model of solar energy plants by ANN and MCDM techniques
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