Support Vector Machine Parameters on Effect of Detection Accuracy
This paper proposed a method according to genetic algorithm and support vector machines aiming at the intrusion detection precision low. By means of which related parameters were optimized, and at the same time, support vector machines model was established based on genetic algorithm, and discussed the effect of the parameters of support vector machines on detection accuracy. At first, this method used genetic algorithm for attribute reduction and optimized the parameters of support vector machine. Then the parameters was put into support vector machine to test the classification of unknown samples. Experiments showed that the parameters of support vector machines were optimized by genetic algorithm, which improved the detection accuracy.
genetic algorithm support vector machine intrusion detection
Li Lan Liu Yue-Ting
School of Electronics and information Engineering, Gansu Lianhe University Lanzhou, Gansu, China
国际会议
成都
英文
416-419
2010-12-17（万方平台首次上网日期，不代表论文的发表时间）