简介:Therecentlyinventedartificialbeecolony(ABC)algorithmisanoptimizationalgorithmbasedonswarmintelligencethathasbeenusedtosolvemanykindsofnumericalfunctionoptimizationproblems.Itperformswellinmostcases,however,therestillexistsaninsufficiencyintheABCalgorithmthatignoresthefitnessofrelatedpairsofindividualsinthemechanismoffindinganeighboringfoodsource.ThispaperpresentsanimprovedABCalgorithmwithmutuallearning(MutualABC)thatadjuststheproducedcandidatefoodsourcewiththehigherfitnessbetweentwoindividualsselectedbyamutuallearningfactor.TheperformanceoftheimprovedMutualABCalgorithmistestedonasetofbenchmarkfunctionsandcomparedwiththebasicABCalgorithmandsomeclassicalversionsofimprovedABCalgorithms.TheexperimentalresultsshowthattheMutualABCalgorithmwithappropriateparametersoutperformsotherABCalgorithmsinmostexperiments.
简介:ArtificialIntelligenceEmbeddedObject-OrientedMethodologyForModelBasedDecisionSupport¥FengShan;TianYuan;LiTong&CaiJun(Institut...
简介:Handwrittensignaturerecognitionispresentedbasedonananglefeaturevectorbyusingtheartificialneuralnetwork(ANN)inthisresearch.Eachsignatureimagewillberepresentedbyananglevector.ThefeaturevectorwillconstitutetheinputtotheANN.Thecollectionofsignatureimagesisdividedintotwosets.OnesetwillbeusedfortrainingtheANNinasupervisedfashion.TheothersetwhichisneverseenbytheANNwillbeusedfortesting.Aftertraining,theANNwillbetestedbyrecognizingthesignatures.Whenasignatureisclassifiedcorrectly,itisconsideredcorrectrecognition,otherwiseitisafailure.Theachievedrecognitionrateofthissystemis94%.