BP神经网络和模糊系统均属于无模型的估计器和非线性动力学系统，也是处理

Both BP neural networks and fuzzy systems belong to model-free estimators and nonlinear dynamic systems, and they are also powerful tools for dealing with uncertainty and nonlinearity. But the characteristics between the two are quite different. The extraction and expression of knowledge in a fuzzy system is more convenient. It is more suitable for expressing those vague or qualitative knowledge. Its reasoning is also similar to human thinking mode, but it lacks self-learning and adaptive capabilities. The neural network can directly learn from the results effectively. It has the advantages of parallel computing, distributed information storage, strong fault tolerance and adaptive learning, but it is not suitable for expressing rule-based knowledge. Absorbing the strengths of each family is the biggest advantage of fuzzy neural networks

Both BP neural network and fuzzy system belong to modelless estimator and nonlinear dynamics system, and are also powerful tools to deal with uncertainty and nonlinearity. But there are big differences in the characteristics between the two. It is convenient to extract and express knowledge in fuzzy system, it is more suitable for expressing those fuzzy or qualitative knowledge, and its reasoning is similar to human thinking mode, but it lacks self-learning and adaptive ability. The neural network can learn effectively from the results directly, and has the advantages of parallel computation, distributed information storage, fault tolerance ability and adaptive learning, but it is not suitable for expressing rule-based knowledge. Drawing on the length of each family is the biggest advantage of fuzzy neural networks.

Both BP neural network and fuzzy system belong to model free estimator and nonlinear dynamic system. They are also powerful tools to deal with uncertainty and nonlinearity. However, there are great differences between the two. The extraction and expression of knowledge in fuzzy system is more convenient, it is more suitable for expressing those fuzzy or qualitative knowledge, and its reasoning is similar to human thinking mode, but it lacks self-learning and self-adaptive ability. However, neural network can learn from the results directly, which has the advantages of parallel computing, distributed information storage, strong fault tolerance and adaptive learning, but it is not suitable to express rule-based knowledge. It is the biggest advantage of fuzzy neural network to absorb the strong points of each school<br>