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Application of GA-SVM in classification of surrounding rock based on model reliability examination 被引量:6

Application of GA-SVM in classification of surrounding rock based on model reliability examination
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摘要 In order to improve the discrimination precision of support vector machine(SVM) in classification of surrounding rock, a Genetic Algorithm(GA) was used to optimize SVM parameters in the solution space.The idea of examination of model reliability was introduced to check the reliability of the SVM parameters,obtained by genetic algorithms.In the process of model reliability,a trend examination method is presented,which checks the reliability of the model via the influence trend of impact factors on the object of evaluation and their evaluation level.Trend examination methods are universal,showing new ideas in model reliability examination and can be used in any problems of examination of reliability of models,based on previous experience.We established a GA-SVM based reliability model of a classification the surrounding rock and applied it to a practical engineering situation.The result shows that the improved SVM has a high capability for generalization and prediction accuracy in classification of surrounding rock. In order to improve the discrimination precision of support vector machine(SVM) in classification of surrounding rock, a Genetic Algorithm(GA) was used to optimize SVM parameters in the solution space.The idea of examination of model reliability was introduced to check the reliability of the SVM parameters,obtained by genetic algorithms.In the process of model reliability,a trend examination method is presented,which checks the reliability of the model via the influence trend of impact factors on the object of evaluation and their evaluation level.Trend examination methods are universal,showing new ideas in model reliability examination and can be used in any problems of examination of reliability of models,based on previous experience.We established a GA-SVM based reliability model of a classification the surrounding rock and applied it to a practical engineering situation.The result shows that the improved SVM has a high capability for generalization and prediction accuracy in classification of surrounding rock.
出处 《Mining Science and Technology》 EI CAS 2010年第3期428-433,共6页 矿业科学技术(英文版)
基金 supported by the Key Project of Ministry of Education (No.108158) the Natural Science Foundation of Shandong Province(No.Y2007F53) the Postdoctoral Science Foundation of China(No.2009 0461203).
关键词 support vector machine classification of surrounding rock RELIABILITY genetic algorithm support vector machine classification of surrounding rock reliability genetic algorithm
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