本文提出了一个面向股市预测的模糊神经网络系统，并针对系统性能的改善进行了深入研究。
This paper puts forward a fuzzy neural network system aimed at stock price prediction, and an ameliorative method on its function is studied.
由于自适应模糊神经网络系统具有非线性映射和自学习能力，能够用于噪声信号的非线性建模。
The AFNNS has the abilities of nonlinear mapping and self-learning property and can be used to achieve the nonlinear model of the noise.
模糊神经网络系统可以根据系统输入输出信号，建立系统的输入输出关系，并对环境的变化具有较强的自适应学习能力。
Fuzzy Neural Network System (FNNS) can construct input? Output relationship by means of input and output signal and FNNS has special characteristics of adaptive learn while environment is changing.
ANFIS设计方法是一种将模糊逻辑系统(FLS)和人工神经网络系统(ann)相结合，利用两者各自的优点所形成的混合智能系统。
The ANFIS design method is a blend intelligent system which combines the Fuzzy Logic system (FLS) and the Annual Neural Network (ANN) and USES their's strongpoints.
ANFIS设计方法是一种将模糊逻辑系统(FLS)和人工神经网络系统(ann)相结合，利用两者各自的优点所形成的混合智能系统。
The ANFIS design method is a blend intelligent system which combines the Fuzzy Logic system (FLS) and the Annual Neural Network (ANN) and USES their's strongpoints.
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