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Energies2018,11, 1009
ranging frompredictable tochaos, i.e.,withgoodergodicuniformity [40]. Thispaper thusapplies
the tent chaoticmapping function to behybridizedwith theCSalgorithm todetermine the three
parametersofanSVRmodel.
The tentchaoticmappingfunction isshownasEquation(8):
xn+1= {
2xn x∈ [0,0.5]
2(1−xn) x∈ (0.5,1] (8)
wherexn is the iterativevalueof thevariablex in thenthstep,andn is thenumberof iterationsteps.
2.2.2.CuckooSearch(CS)Algorithm
TheCSalgorithm is anovelmeta-heuristic optimizationalgorithm, inspiredbycuckoobirds’
obligate broodparasitic behavior of laying their eggs in thenests of otherhost birds. Meanwhile,
byapplyingLévyflightbehaviors, thesearchspeed ismuchfaster thanthatof thenormal random
walk. Therefore, cuckoo birds can reduce the number of iterations and thus speed up the local
searchefficiency. ForCSalgorithmimplementation,eachegg inanest representsapotential solution.
Thecuckoobirdscouldchoose,byLévyflightbehaviors, recently-spawnednests to lay theireggs in
thehostnests toensure theireggscouldhatchfirstdueto thenaturalphenomenonthatcuckooeggs
usuallyhatchbefore thehostbirds’ eggs. It takes times for thehostbirds todiscover that theeggs
in theirnestsdonotbelong to them,basedon theprobability, pa. When these“stranger”eggsare
discovered, theyeither throwout thoseeggsorabandonthewholenest tobuildanewnest inanew
location. Thecuckoobirdswouldcontinuously layneweggs (solutions), andtheywouldchoose the
nest,byLévyflightbehaviors,aroundthecurrentbest solutions.
TheCSalgorithmcontains three famous idealized rules [31]: (1) each cuckoo lays one eggat
a timeinarandomlyselectedhost; (2)high-qualityeggsandtheirhostnestswouldsurvive to thenext
generation; (3) thenumberofavailablehostnests isfixed,andthehostbirddetects the“stranger”egg
withaprobability pa∈ [0,1]. In thiscase, thehostbirdcaneither throwawaytheeggorabandonthe
nest, andbuildacompletelynewnest. The last rulecanbeapproximatedbyafraction(pa)of then
hostnests thatare replacedbynewnests (withnewrandomsolutions). Thevalueof pa isoftenset
as0.25 [37].
TheCS algorithm couldmaintain the balance between twokinds of search (randomwalks),
the local search and theglobal search, by a switchingparameter, pa. The switchingparameter pa
determinesthecuckoobirdstoabandonafractionoftheworstnestsandbuildnewonesfordiscovering
new andmore promising regions in the search space. These two randomwalks are defined by
Equations (9)and(10), respectively:
xt+1i = x t
i+αs⊗H(pa−δ)⊗ (
xtj−xtk )
s (9)
xt+1i = x t
i+αL(s,λ) (10)
where xtj and x t
k are current positions randomly selected; α is the positive Lévy flight step size
scalingfactor; s is thestepsize;H(·) is theHeavy-side function;δ isa randomnumber fromuniform
distribution;⊗ represents theentry-wiseproductof twovectors;L(s,λ) is theLévydistributionandis
usedtodefinethestepsizeof randomwalk, it isdefinedasEquation(11):
L(s,λ)= λΓ(λ)sin(πλ/2)
π 1
s1+λ (11)
where λ is the standard deviation of step size; the gamma function, Γ(λ), is defined as
Γ(λ)= ∫∞
0 t λ−1e−tdt, and represents an extension of factorial function, if λ is a positive integer,
then,Γ(λ)=(λ−1)!. Lévyflightdistributionenablesaseriesofstraight jumpschosenfromanyflight
27
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
- Informatik