Feasibility Model of Solar Energy Plants by ANN and MCDM Techniques

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 prod...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Majumder, Mrinmoy (Συγγραφέας), Saha, Apu K. (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Singapore : Springer Singapore : Imprint: Springer, 2016.
Σειρά:SpringerBriefs in Energy,
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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100 1 |a Majumder, Mrinmoy.  |e author. 
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. 
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300 |a X, 49 p. 14 illus., 13 illus. in color.  |b online resource. 
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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 Energy. 
650 0 |a Renewable energy resources. 
650 0 |a Climate change. 
650 0 |a Electric power production. 
650 0 |a Computational intelligence. 
650 0 |a Renewable energy sources. 
650 0 |a Alternate energy sources. 
650 0 |a Green energy industries. 
650 0 |a Environmental economics. 
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650 2 4 |a Renewable and Green Energy. 
650 2 4 |a Computational Intelligence. 
650 2 4 |a Energy Technology. 
650 2 4 |a Environmental Economics. 
650 2 4 |a Climate Change/Climate Change Impacts. 
700 1 |a Saha, Apu K.  |e author. 
710 2 |a SpringerLink (Online service) 
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776 0 8 |i Printed edition:  |z 9789812873071 
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