The Design And Research Based On Gentic Algorithm Of Workflow Mining

The aim of workflow mining is to establish the explicit workflow model.However current workflow mining algorithms mostly use local strategy,which can not guarantee that a globally optimal workflow model is mined.In addition,these algorithms are not robust when logs contain noise.The genetic algororithms performing global seach can overcome problems,and the promblem of noise is naturally tackled by the genetic algorithms,but it would search search a better workflow model after many iterations.The genetic algorithm is easily premature restraining as well as later period searching efficiency in th evolution to be low.So,In this paper,combined with virus evolutionary mechanism,we propose an improved approach based on the hybrid genetic algorithm,the algorithm introduct the virus population based on the original population that infaction the population of individuals,at the same time the virus itself has certain vitality,So can increase the diversity of the original population,and avoid premature convergence and precocious phenomena. In the workflow virus evolutionary mechanism introduction,need Petri net and causal relationship whith matrix,the population of virus of individuals to chrommosames,set the virus vitality and appealing,and combining with the genetic algorithm in workflow mining on design,the design viruses operators,infection operation and degradation operation,eventually produce a new algorithm.Finally,the paper telled the four model assessment standards,they were:behavior accuracy,behavior recreate degrees,structure accuracy,the structure of return,they were evaluation through the event log mining out of the accurracy of the workflow model combined with integrity,our evaluation based on the results of new algorithm. Through the mining of38event log,the experiment shows that,no matter form integrity or from the accuracy evaluation assessment,the new algorithm can always dig out the traditional algorithm better than the workflow model.