摘要
针对股价系统内部结构的复杂性、外部因素的多变性,分析了自适应神经模糊系统,并对股市建立预测模型。ANFIS是把神经网络和T-S模糊推理结合在一起的系统,从而克服了模糊理论不具备自学习能力和神经网络无法表达人类自然语言的缺点。对金融股指进行预测,以最具代表性的上证指数为例,通过ANFIS算法仿真实验分析,表明了该算法能够有效、可靠预测上证指数走势,并且能够将金融系统模糊规则明确,揭示金融系统运行模式。
Aiming at the complexity of inside structure and levity of exterior complication in system of stock market which make stock market prediction a complex problem, a method of modeling Adaptive Network - based Fuzzy Inference System that is based on thorough study of the difficult problems facing stock predication is proposed. ANFIS is a System combined with artificial neural network and T - S fuzzy Inference which overcomes fuzzy theorem couldn＇ t self - study and neural network couldn＇t express human language. ANFIS algorithm can effectively and reliably be used in prediction of the Shanghai stock index, and get fuzzy inference rules which can explain how the Finance System run.
出处
《经济问题》
CSSCI
北大核心
2009年第11期91-96,99,共7页
On Economic Problems
关键词
股票指数预测
模糊逻辑系统
自适应神经网络
T—S模糊推理
stock index prediction
Neuro - Fuzzy Inference System
Adaptive neural network
T- S Fuzzy Inference
