Application of improved genetic algorithm in the evaluation system of enterprise
In this paper, in order to solve the problem of intelligent test paper, the author puts forward the improvement on chromosome coding, mutation algorithm and genetic operators of genetic algorithm after the study of genetic algorithm in theory and then proposes a multi-objective function optimization...
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| Vydáno v: | 2015 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC) s. 1 - 4 |
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| Hlavní autoři: | , |
| Médium: | Konferenční příspěvek |
| Jazyk: | angličtina |
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IEEE
01.09.2015
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| ISBN: | 1479989185, 9781479989188 |
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| Abstract | In this paper, in order to solve the problem of intelligent test paper, the author puts forward the improvement on chromosome coding, mutation algorithm and genetic operators of genetic algorithm after the study of genetic algorithm in theory and then proposes a multi-objective function optimization algorithm. By experimental simulation, it is concluded that, compared with the ordinary genetic algorithm, the average fitness value of the improved algorithm has increased, moreover the average number of iterations and the time consumption has reduced. What's more, when the improved algorithm is applied to the enterprise appraisal, it is proved by experiments that the advantage of low repetition rate to realize the intelligent test paper, the success rate of test paper is 100%, and the repetition rate is 0.9%. Thus the superiority of the improved algorithm is reflected very well. |
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| AbstractList | In this paper, in order to solve the problem of intelligent test paper, the author puts forward the improvement on chromosome coding, mutation algorithm and genetic operators of genetic algorithm after the study of genetic algorithm in theory and then proposes a multi-objective function optimization algorithm. By experimental simulation, it is concluded that, compared with the ordinary genetic algorithm, the average fitness value of the improved algorithm has increased, moreover the average number of iterations and the time consumption has reduced. What's more, when the improved algorithm is applied to the enterprise appraisal, it is proved by experiments that the advantage of low repetition rate to realize the intelligent test paper, the success rate of test paper is 100%, and the repetition rate is 0.9%. Thus the superiority of the improved algorithm is reflected very well. |
| Author | Tian Yu-tong Han Xiao-bing |
| Author_xml | – sequence: 1 surname: Han Xiao-bing fullname: Han Xiao-bing organization: Commun. & Inf. Eng. Coll., Xi'an Univ. of Sci. & Technol., Xi'an, China – sequence: 2 surname: Tian Yu-tong fullname: Tian Yu-tong organization: Commun. & Inf. Eng. Coll., Xi'an Univ. of Sci. & Technol., Xi'an, China |
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| Snippet | In this paper, in order to solve the problem of intelligent test paper, the author puts forward the improvement on chromosome coding, mutation algorithm and... |
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| SubjectTerms | Algorithm design and analysis Artificial intelligence Biological cells chromosome coding Encoding Genetic algorithms intelligent test paper multi-objective function optimization Sociology Statistics The improved genetic algorithm |
| Title | Application of improved genetic algorithm in the evaluation system of enterprise |
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