Genetic Algorithm And Its Application In Network Information Filtering Research

Genetic Algorithm is an adaptively intelligent optimization algorithm developed fromevolution selection mechanism in biological universe. It is suitable for use in the traditionalalgorithm such as complex problems and nonlinear problems which are more difficult to solve .The greatest feature of genetic algorithms is the hidden nature in parallel computing and theglobal search nature in problem solving. Currently, the relevant research for genetic algorithmand its application are a hot area of intelligent computing field.Network information filtering technology came into being with the network’s continualevolution. As the network continues to develop, all kinds of applications followed and theinformation transmitted by network also becomes confusing. There is no doubt that networkmakes our spiritual and material life rich, however there are also other types of undesirableinformation’s appearance. Meanwhile, the huge amount of network information also makes itdifficult for users to locate and access the information they need quickly and accurately. Networkinformation filtering technologies are born to address the issue, which mainly do research on theproblems such as the access and denotation for network information, the user template’s building,and document classification and so on.This paper conducted a study of genetic algorithm firstly, and then proposed a strategybased on segmentation mutation operator for its shortcomings to improve the thinking. On thisbasis, the improved genetic algorithm were applied into user template’s building blocks innetwork information filter .In this paper, the main works are as followed:1. Conduct a study and discussion on genetic algorithm and propose an algorithm toimprove it.This paper explored the basic principles and applications of genetic algorithms in depth andgave a summary in areas including the source, the development process and the basic elements.The characteristics of the genetic algorithm are given and the basic genetic algorithm’s processwas also described. To aim at improving the inherent defection in genetic algorithm, an improvedstrategy based on segmentation mutation operator has been proposed. Comparison tests werecarried out on MATLAB platform by common test functions.2. The improved genetic algorithm has been applied to the template’s optimization ofnetwork information filtering.On the basis of the in-depth study on varieties of key technologies in network informationfiltering, the improved genetic algorithm was implied to optimize the template, which enhancedthe expression capabilities of class template and improved the classification accuracy.3. Combining with genetic algorithm, a network information filtering system has been designed and implemented.Text used the improved genetic algorithm to train documents and to build type template,and then used classification algorithm to classify the classification testing text, which eventuallyachieved a network information filtering system which was proved to be stable, reliable and beable to efficiently complete classification and filtering of network information.