LEADER 03587nam 22007935 450 001 9910253992703321 005 20251113212131.0 010 $a981-287-308-2 024 7 $a10.1007/978-981-287-308-8 035 $a(CKB)3710000000653762 035 $a(EBL)4517737 035 $a(SSID)ssj0001665958 035 $a(PQKBManifestationID)16455724 035 $a(PQKBTitleCode)TC0001665958 035 $a(PQKBWorkID)15000869 035 $a(PQKB)11071595 035 $a(DE-He213)978-981-287-308-8 035 $a(MiAaPQ)EBC4517737 035 $a(PPN)193442728 035 $a(EXLCZ)993710000000653762 100 $a20160429d2016 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aFeasibility Model of Solar Energy Plants by ANN and MCDM Techniques /$fby Mrinmoy Majumder, Apu K. Saha 205 $a1st ed. 2016. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2016. 215 $a1 online resource (58 p.) 225 1 $aSpringerBriefs in Energy,$x2191-5539 300 $aDescription based upon print version of record. 311 08$a981-287-307-4 320 $aIncludes bibliographical references at the end of each chapters. 327 $aIntroduction -- 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. 330 $aThis Brief highlights a novel model to find out the feasibility of any location to produce solar energy. The model utilizes the latest multi-criteria decision making techniques and artificial neural networks to predict the suitability of a location to maximize allocation of available energy for producing optimal amount of electricity which will satisfy the demand from the market. According to the results of the case studies further applications are encouraged. 410 0$aSpringerBriefs in Energy,$x2191-5539 606 $aRenewable energy sources 606 $aComputational intelligence 606 $aElectric power production 606 $aEnvironmental economics 606 $aClimatology 606 $aRenewable Energy 606 $aComputational Intelligence 606 $aElectrical Power Engineering 606 $aMechanical Power Engineering 606 $aEnvironmental Economics 606 $aClimate Sciences 615 0$aRenewable energy sources. 615 0$aComputational intelligence. 615 0$aElectric power production. 615 0$aEnvironmental economics. 615 0$aClimatology. 615 14$aRenewable Energy. 615 24$aComputational Intelligence. 615 24$aElectrical Power Engineering. 615 24$aMechanical Power Engineering. 615 24$aEnvironmental Economics. 615 24$aClimate Sciences. 676 $a621.042 700 $aMajumder$b Mrinmoy$4aut$4http://id.loc.gov/vocabulary/relators/aut$0875357 702 $aSaha$b Apu K$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910253992703321 996 $aFeasibility Model of Solar Energy Plants by ANN and MCDM Techniques$92294371 997 $aUNINA