| Summary: | 碩士 === 元智大學 === 工業工程與管理學系 === 94 === The stock market is very important to the economic development of a country, because it will influence the general industry and economic development system of a country. Therefore, in this search we are trying to combine the neural network technique and case base reasoning technique to construct a trading system. Besides we will provide strategy of the stock selection decision. There are two steps in the prediction model: First step is neural network model, in which we use back-propagation network to train input data, in which the output data are buy-sell point; Second step is case-base reasoning model, in which we use dynamic time window search to retrieve history patten and find the most similar neighbouring solution in order to predict stock trading. The result of our experiment shows that our stock selection strategy can find investment ambition for increasing profits. Therefor case-base reasoning can help neural network model to determine the best tradind point.
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