|Table of Contents|

PredictionofCriticalDepositionVelocityinSlurryPipelineBasedonImprovedABC-LSSVM(PDF)

《南京师大学报(自然科学版)》[ISSN:1001-4616/CN:32-1239/N]

Issue:
2020年01期
Page:
136-142
Research Field:
·计算机科学与技术·
Publishing date:

Info

Title:
PredictionofCriticalDepositionVelocityinSlurryPipelineBasedonImprovedABC-LSSVM
Author(s):
YangJingzong1YangTianqing1ZhouChengjiang2PanAnning1
(1.SchoolofInformation,BaoshanUniversity,Baoshan678000,China)(2.SchoolofInformationEngineeringandAutomationChemistry,KunmingUniversityofTechnology,Kunming650500,China)
Keywords:
criticaldepositionvelocityslurrypipelinesABCLSSVM
PACS:
TP181
DOI:
10.3969/j.issn.1001-4616.2020.01.020
Abstract:
Aimingatthedifficultyofpredictingthecriticaldepositionvelocityinslurrypipelineandthecomplexityofcalculation,thispaperintroducedtheimprovedartificialbeecolonyalgorithm(ABC)tooptimizetheleastsquaressupportvectormachine(LSSVM)forpredictingthecriticaldepositionvelocity.Inordertobalancethelocalsearchandglobalsearchperformanceofthealgorithm,thebeesintheimprovedalgorithmrefertotheglobalcurrentoptimalsolutionofhiredbeesandtheindividualcurrentoptimalsolution.Thesimulationresultsshowthattheproposedmethodismoreaccuratethantheconventionalmethod.Themeansquarerooterror,averagerelativeerrorandaverageabsoluteerrorareonly3.05%,1.00%and2.06%respectively.Meanwhile,itissuperiortothetraditionalempiricalformulaforcalculatingcriticaldepositionvelocity.

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Last Update: 2020-03-15