Seite - 21 - in Short-Term Load Forecasting by Artificial Intelligent Technologies

Energies2018,11, 2226 18. Hong,W.C.Electric loadforecastingbyseasonal recurrentLS-SVR(supportvector regression)withchaotic artificialbeecolonyalgorithm.Energy2011,36, 5568–5578. [CrossRef] 19. Fan,G.F.;Peng,L.L.;Zhao,X.;Hong,W.C.ApplicationsofhybridEMDwithPSOandGAforanSVR-based loadforecastingmodel.Energies2017,10, 1713. [CrossRef] 20. Suykens, J.A.K.;Vanddewalle, J.Least squaressupportvectormachinesclassifiers.NeuralNetw. Lett. 1999, 19, 293–300. [CrossRef] 21. Wang, J.; Hu, J. A robust combination approach for short-term wind speed forecasting and analysis—CombinationoftheARIMA(AutoregressiveIntegratedMovingAverage),ELM(ExtremeLearning Machine),SVM(SupportVectorMachine)andLSSVM(LeastSquareSVM)forecastsusingaGPR(Gaussian ProcessRegression)model.Energy2015,93, 41–56. 22. Hong,W.C.;Dong,Y.;Zhang,W.;Chen,L.Y.; Panigrahi,B.K.Cyclic electric load forecastingbyseasonal LS-SVRwithchaoticgeneticalgorithm. Int. J.Electr. PowerEnergySyst. 2013,44, 604–614. [CrossRef] 23. Ju,F.Y.;Hong,W.C.ApplicationofseasonalSVRwithchaoticgravitationalsearchalgorithminelectricity forecasting.Appl.Math.Model. 2013,37, 9643–9651. [CrossRef] 24. Fan,G.;Peng,L.L.;Hong,W.C.;Sun,F.Electric loadforecastingbytheSVRmodelwithdifferentialempirical modedecompositionandautoregression.Neurocomputing2016,173, 958–970. [CrossRef] 25. Pan,W.T.FruitFlyOptimizationAlgorithm;TsanghaiPublishing: Taipei,Taiwan,China,2011. 26. Pan,W.T. A new fruit fly optimization algorithm: Taking the financial distressmodel as an example. Knowl.-BasedSyst. 2012,26, 69–74. [CrossRef] 27. Mitic´,M.;Vukovic´,N.;Petrovic´,M.;Miljkovic´,Z.Chaotic fruitflyoptimizationalgorithm.Knowl.-BasedSyst. 2015,89, 446–458. [CrossRef] 28. Wu,L.;Liu,Q.;Tian,X.;Zhang, J.;Xiao,W.AnewimprovedfruitflyoptimizationalgorithmIAFOAandits applicationtosolveengineeringoptimizationproblems.Knowl.-BasedSyst. 2018,144, 153–173. [CrossRef] 29. Han, X.; Liu, Q.; Wang, H.; Wang, L. Novel fruit fly optimization algorithm with trend search and co-evolution.Knowl.-BasedSyst. 2018,141, 1–17. [CrossRef] 30. Zhang,X.;Lu,X.; Jia,S.;Li,X.Anovelphaseangle-encodedfruitflyoptimizationalgorithmwithmutation adaptationmechanismappliedtoUAVpathplanning.Appl. SoftComput. 2018,70, 371–388. [CrossRef] 31. Han,S.Z.;Pan,W.T.;Zhou,Y.Y.;Liu,Z.L.Construct thepredictionmodel forChinaagriculturaloutputvalue basedontheoptimizationneuralnetworkof fruitflyoptimizationalgorithm.FutureGener. Comput. Syst. 2018,86, 663–669. [CrossRef] 32. Yang,X.S.;Gandomi,A.H.Batalgorithm:Anovelapproachforglobalengineeringoptimization.Eng.Comput. 2012,29, 464–483. [CrossRef] 33. Narayanan,A.;Moore,M.Quantum-inspiredgeneticalgorithms. InProceedingsof the IEEEInternational ConferenceonEvolutionaryComputation,Nagoya, Japan,20–22May1996;pp.61–66. 34. Han,K.H.;Kim, J.H.Geneticquantumalgorithmanditsapplication tocombinatorialoptimizationproblem. InProceedingsof the 2000CongressonEvolutionaryComputation, La Jolla,CA,USA, 16–19 July2000; pp.1354–1360. 35. Han,K.H.;Kim, J.H.Quantum-inspiredevolutionaryalgorithmforaclassofcombinatorialoptimization. IEEETrans. Evol. Comput. 2002,6, 580–593. [CrossRef] 36. Huang,M.L.HybridizationofchaoticquantumparticleswarmoptimizationwithSVRinelectricdemand forecasting.Energies2016,9, 426. [CrossRef] 37. Lee,C.W.; Lin,B.Y.Applicationofhybridquantumtabusearchwith support vector regression for load forecasting.Energies2016,9, 873. [CrossRef] 38. Lee,C.W.;Lin,B.Y.Applicationsof thechaoticquantumgeneticalgorithmwithsupportvector regression in loadforecasting.Energies2017,10, 1832. [CrossRef] 39. Li,M.W.;Geng, J.;Wang,S.;Hong,W.C.HybridchaoticquantumbatalgorithmwithSVRinelectric load forecasting.Energies2017,10, 2180. [CrossRef] 40. Shi,D.Y.;Lu,L.J.A judgemodelof the impactof laneclosure incidenton individualvehiclesonfreeways basedonRFIDtechnologyandFOA-GRNNmethod. J.WuhanUniv. Technol. 2012,34, 63–68. 41. Yuan,X.;Wang,P.; Yuan,Y.;Huang,Y.; Zhang,X.Anewquantuminspiredchaotic artificial bee colony algorithmforoptimalpowerflowproblem.EnergyConvers.Manag. 2015,100, 1–9. [CrossRef] 42. Peng,A.N.Particle swarmoptimizationalgorithmbasedonchaotic theoryandadaptive inertiaweight. J.Nanoelectron.Optoelectron. 2017,12, 404–408. [CrossRef] 21