摘要
提出一种将粒子群优化(PSO)和FCM相结合的聚类算法PSOFCA对入侵检测系统进行研究,克服FCM方法自身对初始值敏感、容易陷入局部最优等问题。最后对实验数据进行仿真实验,并将实验结果与其他算法结果相比较,结果表明PSOFCA算法在入侵检测中能获得较好的检测能力。
A Particle Swarm Optimization-based Fuzzy Clustering Algorithms （PSOFCA） is proposed to improve some defects of sensitivity to the initial data,getting in the local optimization and so on about Fuzzy C-Means in intrusion detection system.Finally,the empirical datum is simulated,and the computational results compares with other algorithm results.The compared results show a better detective ability than other algorithms by the data obtained in experiment.
出处
《计算机工程与应用》
CSCD
北大核心
2008年第2期149-151,共3页
Computer Engineering and Applications
基金
国家高技术研究发展计划( 863)( the National High-Tech Research and Development Plan of China under Grant No.2006AA04Z131) 。
