中文摘要：

基于数据挖掘思想，运用模糊集合理论和改进的梯度下降方法，提出一种通用的、同时辨识模糊模型、调整其参数及确定输出变量空间最优划分的新方法，该方法不仅能够修剪冗余和冲突的初始模糊规则，而且通过引入动态误差传递因子，解决了梯度下降法中存在的收敛速度和振荡之间的冲突问题，用经典的倒车控制问题进行了验证，仿真结果表明了本方法的有效性和准确性。

英文摘要：

On the basis of data mining, a new method is developed for identifying fuzzy model, updating its parameters and determining optimal division of output space simultaneously by means of fuzzy sets theory and the improved gradient descent method. The method can not only prune the redundant and conflicted initial fuzzy rules, but also resolve the conflicts of convergence speed and oscillation existing in gradient descent method by introducing dynamic error transfer factor. The simulation results show the effectiveness and the accuracy of the proposed method by the verification of the classical truck backer-upper control problem.