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Short-Term Load Forecasting by Artificial Intelligent Technologies
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Energies2018,11, 1253 In the first stage of this algorithm, 2n lions are averagely assigned to two groups as the candidate population, namely male lions Am = [ ψm1 ,ψ m 2 ,ψ m 3 , · · · ,ψml ] and female lions Af = [ ψ f 1,ψ f 2,ψ f 3, · · · ,ψfl ] . l represents the lengthof thesolutionvector. Step2:Mating Mating isanessentialprocess toupdateandmaintain thestabilityof the liongroupviacrossover, mutation, cluster or killing the sick andweak, thus new solutions can be continually delivered throughiteration. Dual probabilities based crossover is introduced in this paper, that is, crossover is implementedwith two different probabilities. The lion Am and lioness Af generate a new cub Acub= [ ψcub1 ,ψ cub 2 ,ψ cub 3 , · · · ,ψcubl ] throughmating. Then, fourcubsAcub1∼4 aregeneratedaccordingto tworandomlyselectedcrossoverpointsbyψmi andψ f j . Random mutation with p is enabled to generate Acub5∼8, resulting in 8 cubs after crossover andmutation. Thecubsareseparated intomalecubs (Am_cub) andfemalecubs (Af_cub)byK-meansclustering. Then, in lightofhealth status, theweakcubs in largergrouparekilledoff to ensureanequal number in the twocubs.Afterpopulationregeneration, theageof thecubis initializedas0. Step3: Territorialdefense Duringbreeding, itwillbeattackedbythenomadic lion.At this time, themale lionwilldefend andprotect thecubs,andoccupythe territory,as illustrated inFigure1. Territorial lion Lioness New adult territorial lion Swimming lion Figure1.Liondefenseprocess. Thenomadic lionψnomad isgenerated in thewaythat is thesameas territorial lion. Thenthenew solutionψnomad isusedtoattack themale lionψmi . Ifψ nomad is superior toothersolutions in thepride, replaceψmi withψ nomad. Thenewlionwill continuetomate,andtheold,aswellas thecubs,willbe killedoff.Otherwise, theold lionwill continuewith territorydefense,andthecubswillbeoneyear older thanbefore. f(·) is theobjective functionand f ( ψpride ) is thevalueof thewholepopulationwhichcanbe calculatedasEquation(2). f ( ψpride ) = 1 2 ( 1+‖ψm_cub‖) ⎛⎝f(ψm)+ f(ψf)+ agemat agecub+1 · ‖ψm_cub‖ ∑ k=1 f ( ψm_cubk ) + f ( ψ f_cub k ) ‖ψm_cub‖ ⎞⎠ (2) 357
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Short-Term Load Forecasting by Artificial Intelligent Technologies
Titel
Short-Term Load Forecasting by Artificial Intelligent Technologies
Autoren
Wei-Chiang Hong
Ming-Wei Li
Guo-Feng Fan
Herausgeber
MDPI
Ort
Basel
Datum
2019
Sprache
englisch
Lizenz
CC BY 4.0
ISBN
978-3-03897-583-0
Abmessungen
17.0 x 24.4 cm
Seiten
448
Schlagwörter
Scheduling Problems in Logistics, Transport, Timetabling, Sports, Healthcare, Engineering, Energy Management
Kategorie
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Short-Term Load Forecasting by Artificial Intelligent Technologies