双层模糊系统融合中心约束型最小包含球

与传统的TSK模糊系统相比,改进的双层TSK模糊系统CTSK(Central TSK Fuzzy System)有如下优点:良好的可解释性、更好的鲁棒性、较强的逼近能力。但对于大样本或超大样本数据集,其时间复杂度和空间复杂度的开销都极大地限制了它的实用性。针对此不足,通过模糊系统融合中心约束型最小包含球(CCMEB)理论提出了CCMEB-CTSK(CCMEB-based CTSK)算法。该算法在继承CTSK优点的同时,又较好地实现了处理大样本和超大样本数据集的有效性和快速性。仿真实验研究分析了采用不同模糊规则数的CCMEB-CTSK的性能指标和运行时间的比较,以及训练样本不加噪声和加入噪声情况下CCMEB-CTSK泛化能力和鲁棒性能的测试。

Integration of Dual-layer Fuzzy System with Center-constrained Minimal Enclosing Ball

This paper used the central TSK fuzzy system which is the improved double layer TSK fuzzy system.Compared with the traditional TSK fuzzy system,the CTSK fuzzy system(Centralized TSK Fuzzy System)adopts the upgraded dual-layer TSK fuzzy system and has the following advantages:better interpretability,stronger robustness and approximation capability.However,the time and space complexity overhead greatly limits large or super large data sets.In the light of this limitation,a new algorithm CCMEB-CTSK(CCMEB-based CTSK) was proposed here dealing with large data sets.The algorithm not only preserves the advantages of the CTSK fuzzy system,but also contributes to the high efficiency and rapidity in handling large and super large sample data sets.Through simulation experiments,an ana-lysis of the difference in the performance index and running time of CCEMB-CTSK was made,including different fuzzy rule numbers as well as the difference in the generalization capability and performance robustness of CCEMB-CTSK in noiseless and noisy training samples.