The Study About Intelligent Manufacturing Resource Allocation Efficiency Based On Mutual Information Criterion

With the appearance of “Internet +”,the "Internet + Manufacturing Mode",which combines the Internet technology with manufacturing industry,has become a hotspot.This mode realizes the optimal allocation of manufacturing resources through the network platform.On the Internet platform,all resources are present in the form of data,the core of resources allocation is the process and fusion of data,the allocation efficiency of manufacturing resource actually is the efficiency of matching data.The effect of resource allocation is measured mainly by two indicators,one is the rate of resource allocation,another is the accuracy of resource allocation.At present,domestic and foreign scholars use more intelligent algorithms or operations research study Resource Allocation Model,however,these studies are based on the assumption of definite resource environment,they think the attribute of resource is single,but one of the important features of the intelligent manufacturing is uncertainty manufacturing,with the big data and multi-attribute isomerization of manufacturing resources.All of these result in low rate and accuracy of resources allocation In intelligent manufacturing environment,which can't meet the need of multiple attribute and.configuring the massive resources of intelligent manufacturing.From the perspective of data matching,the study about data process of resource is less.These problems have led to a lower efficiency of resource allocation.Based on the above-described problems,this paper mainly highlights the research about the efficiency of resources matching from the internet perspective,putting forward the concept of "resource that is data".Combined with data redundancy issues,starting from the point of Attribute characteristic angle of intelligent manufacturing resources system,this paper separates a large number of unordered resources features elements into the redundant elements of resources and nuclear elements of resources.It researches the distribution of attribute elements variables in the intelligent manufacturing data set information entropy,researches the redundancy elements among the attribute variables with mutual information and studies the feature elements selection mechanism with property features redundancy criterion based on mutual information.This method can eliminate redundancy elements and gain the optimized feature elements set.It also can put these features in order accord to their importance.Then,we can find the resource with robust property features quickly and accurately from the mass of intelligent manufacturing resources.At last,we verify the validity of the attributes feature elements selection model by computer simulation analysis.