Abstract: Rough set integrated neural network method reflects the human’s normal thinking mechanism which mixes the method of quantitative and qualitative,clear and uncertain,serial and parallel.This paper bulids such a model which using rough set’s 2 dimenation reduction ability to reduce the noise and redundence in the samples.So it improves the neural network’s forecasting accuracy as well as reducing its burden of learning.GA is also used in this paper to the attribute’s discretion and neural network learning to find the optimized forecasting accuracy.Case study shows the hybrid model is more competitive than the similar neural network model.

Key words: rough set, neural network, genetic algorithms, stock market, forecast