國立虎尾科技大學 |

Feasibility model of solar energy plants by ANN and MCDM techniques

紀錄類型:	書目-語言資料,印刷品 : 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.;
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:

1107829
Solar energy
--Computer simulation.

LC Class. No.: TJ810

Dewey Class. No.: 621.471

Feasibility model of solar energy plants by ANN and MCDM techniques
LDR:01970nam a2200325 a 4500 001 863635
003 DE-He213
005 20161006135432.0
006 m d
007 cr nn 008maaau
008 170720s2016 si s 0 eng d
020 $a 9789812873088 $q (electronic bk.)
020 $a 9789812873071 $q (paper)
024 7 $a 10.1007/978-981-287-308-8 $2 doi
035 $a 978-981-287-308-8
040 $a GP $c GP
041 0 $a eng
050 4 $a TJ810
072 7 $a THX $2 bicssc
072 7 $a TEC031010 $2 bisacsh
082 0 4 $a 621.471 $2 23
090 $a TJ810 $b .M234 2016
100 1 $a Majumder, Mrinmoy. $3 1076479
245 1 0 $a Feasibility model of solar energy plants by ANN and MCDM techniques $h [electronic resource] / $c by Mrinmoy Majumder, Apu K. Saha.
260 $a Singapore : $c 2016. $b Springer Singapore : $b Imprint: Springer,
300 $a x, 49 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a SpringerBriefs in energy, $x 2191-5520
505 0 $a 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.
520 $a 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.
650 0 $a Solar energy $x Computer simulation. $3 1107829
650 0 $a Solar energy $x Decision making. $3 1107830
650 1 4 $a Energy. $3 784773
650 2 4 $a Renewable and Green Energy. $3 683875
650 2 4 $a Computational Intelligence. $3 768837
650 2 4 $a Energy Technology. $3 768691
650 2 4 $a Environmental Economics. $3 668788
650 2 4 $a Climate Change/Climate Change Impacts. $3 1023634
700 1 $a Saha, Apu K. $3 1107828
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer eBooks
830 0 $a SpringerBriefs in energy. $3 892218
856 4 0 $u http://dx.doi.org/10.1007/978-981-287-308-8
950 $a Energy (Springer-40367)