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010   $a3-030-36529-8
024 7 $a10.1007/978-3-030-36529-5
035   $a(CKB)4940000000159085
035   $a(DE-He213)978-3-030-36529-5
035   $a(MiAaPQ)EBC6005215
035   $a(PPN)242848850
035   $a(EXLCZ)994940000000159085
100   $a20200101d2020      u|         0
101 0 $aeng
135   $aurnn|008mamaa
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aHybrid Intelligent Technologies in Energy Demand Forecasting /$fby Wei-Chiang Hong
205   $a1st ed. 2020.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2020.
215   $a1 online resource (XII, 179 p. 60 illus., 51 illus. in color.) 
311   $a3-030-36528-X 
327   $aIntroduction -- Modeling for Energy Demand Forecasting -- Data Pre-processing Methods -- Hybridizing Meta-heuristic Algorithms with CMM and QCM for SVR?s Parameters Determination -- Hybridizing QCM with Dragonfly algorithm to Enrich the Solution Searching Be-haviors -- Phase Space Reconstruction and Recurrence Plot Theory .
330   $aThis book is written for researchers and postgraduates who are interested in developing high-accurate energy demand forecasting models that outperform traditional models by hybridizing intelligent technologies. It covers meta-heuristic algorithms, chaotic mapping mechanism, quantum computing mechanism, recurrent mechanisms, phase space reconstruction, and recurrence plot theory. The book clearly illustrates how these intelligent technologies could be hybridized with those traditional forecasting models. This book provides many figures to deonstrate how these hybrid intelligent technologies are being applied to exceed the limitations of existing models.
606   $aEnergy policy
606   $aEnergy and state
606   $aComputational intelligence
606   $aComputer simulation
606   $aStatistical physics
606   $aRenewable energy resources
606   $aEnergy Policy, Economics and Management$3https://scigraph.springernature.com/ontologies/product-market-codes/112000
606   $aComputational Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/T11014
606   $aSimulation and Modeling$3https://scigraph.springernature.com/ontologies/product-market-codes/I19000
606   $aApplications of Nonlinear Dynamics and Chaos Theory$3https://scigraph.springernature.com/ontologies/product-market-codes/P33020
606   $aRenewable and Green Energy$3https://scigraph.springernature.com/ontologies/product-market-codes/111000
615  0$aEnergy policy.
615  0$aEnergy and state.
615  0$aComputational intelligence.
615  0$aComputer simulation.
615  0$aStatistical physics.
615  0$aRenewable energy resources.
615 14$aEnergy Policy, Economics and Management.
615 24$aComputational Intelligence.
615 24$aSimulation and Modeling.
615 24$aApplications of Nonlinear Dynamics and Chaos Theory.
615 24$aRenewable and Green Energy.
676   $a006.3
700   $aHong$b Wei-Chiang$4aut$4http://id.loc.gov/vocabulary/relators/aut$0913784
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910373947203321
996   $aHybrid Intelligent Technologies in Energy Demand Forecasting$92147609
997   $aUNINA