Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  presents a hybrid approach to extract compact Takagi-Sugeno fuzzy models from numeric data, using subtractive clustering (SC), particle swarm optimization (PSO) and least square method. The feature of this method lies in the following: (1) the input space is partitioned and initial fuzzy rule bases are extracted by SC; (2) the optimal parameters of the membership functions are evolved by PSO, based on the initial fuzzy rule bases; (3) the consequent parameters of the rule base are analytically derived by the Moore-Penrose pseudo inverse, instead of being iteratively tuned. Simulation results in Mackey-Glass chaotic time series prediction and nonlinear plant modeling problems show that the proposed method is effective and robust in finding compact and accurate T-S fuzzy models.
['Honggang Wang', 'Liang Zhao', 'Wenli Du', 'Feng Qian']
I am writing a research paper on a idea A hybrid method for identifying T-S fuzzy models
[{"from": "human", "value": "I am writing a research paper on a idea A hybrid method for identifying T-S fuzzy models"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  presents a hybrid approach to extract compact Takagi-Sugeno fuzzy models from numeric data, using subtractive clustering (SC), particle swarm optimization (PSO) and least square method. The feature of this method lies in the following: (1) the input space is partitioned and initial fuzzy rule bases are extracted by SC; (2) the optimal parameters of the membership functions are evolved by PSO, based on the initial fuzzy rule bases; (3) the consequent parameters of the rule base are analytically derived by the Moore-Penrose pseudo inverse, instead of being iteratively tuned. Simulation results in Mackey-Glass chaotic time series prediction and nonlinear plant modeling problems show that the proposed method is effective and robust in finding compact and accurate T-S fuzzy models."}]