The application of fuzzy neural networks in stock price forecasting based On Genetic Algorithm discovering fuzzy rules

This paper proposes some methods to improve black-box model considering problems existed in its application. The improvement is achieved mainly by applying GA (Genetic Algorithm) in fuzzy systems to discover rules, eliminate errors or invalid rules caused by noisy data, and thus form valid sets of rules. Evaluation of the rule sets, as that of the whole prediction model, is performed through known knowledge and theories. At last, fuzzy reasoning approach is used based on the rule sets to predict price trend of stock market.

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