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IFP_FCM
简介：IFP_FCM,改进型FCM(模糊C均值)聚类算法,由Frank Hoppner与Frank Klawonn于2003年提出,解决了FCM算法对初始值设定较为敏感、训练速度慢、在迭代时容易陷入局部极小的问题。并附带了Box和Jenkins煤气炉数据模型辨识实例。
文件清单：
IFP_FCM算法原始论文：
Improved fuzzy partitions for fuzzy regression models.pdf
程序清单：
IFP_FCM.m - IFP_FCM算法主函数
initifp_fcm.m - initifp_fcm子函数
stepifp_fcm.m - stepifp_fcm子函数
distifp_fcm.m - distifp_fcm子函数
IFP_FCM_T_S_box_test.m - IFP_FCM测试实例：Box和Jenkins煤气炉数据T-S模糊模型辨识
数据文件：
box_data.mat - Box和Jenkins煤气炉数据(IFP_FCM, modified FCM (Fuzzy C-Means) clustering algorithm, in 2003, proposed by Frank Hoppner and Frank Klawonn, FCM algorithm to solve the initial value setting is more sensitive, slow training, while iterating easy to fall into local minimum problem. And comes with Box and Jenkins gas furnace model identification data instance.)
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- 积分：1
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AssignmentDMC
FUNCTION FILE DMC VARIABLES
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matlabchengxu
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