关键词: 模糊粗糙神经网络, 决策逻辑, 混沌搜索算法, 最小二乘法, 粗糙集

Abstract: A new fuzzy rough neural network modeling method based on decision logic was presented to construct the prediction model of some properties from experiment data. Firstly, the original data was pre-processed and attributes were simplified based on rough set theory to obtain the simplest decision table. Then a fuzzy rough neural network was constructed based on decision logic. Finally, the algorithm Chaos-LS which combined the chaotic search algorithm and least square algorithm was proposed to train the parameters of the fuzzy rough neural network. By this method, a fuzzy rough neural network model was constructed. Simulation results showed that the fuzzy rough neural network model constructed by the modeling method had excellent performance both on accuracy and generalization ability.

Key words: fuzzy rough neural network, decision logic, chaotic search algorithm, least square algorithm, rough set