document: Hybrid fuzzy modeling of chemical processes Fuzzy models have been proved to have the ability of modeling all plants without any priori information . However , the performance of conventional fuzzy models can be very poor in the case of insufficient training data due to their poor extrapolation capacity . In order to overcome this problem , a hybrid grey-box fuzzy modeling approach is proposed in this paper to combine expert experience , local linear models and historical data into a uniform framework . It consists of two layers . The expert fuzzy model constructed from linguistic information , the local linear model and the T-S type fuzzy model constructed from data are all put in the first layer . Layer 2 is a fuzzy decision module that is used to decide which model in the first layer should be employed to make the final prediction . The output of the second layer is the output of the hybrid fuzzy model . With the help of the linguistic information , the poor extrapolation capacity problem caused by sparse training data for conventional fuzzy models can be overcome . Simulation result for pH neutralization process demonstrates its modeling ability over the linear models , the expert fuzzy model and the conventional fuzzy model
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extractive_keyphrases: fuzzy modeling chemical processes expert fuzzy model fuzzy decision module
abstractive_keyphrases: process modeling