| Summary: | 碩士 === 國立臺北大學 === 資訊工程學系 === 100 === As information technology grows dramatically and the financial market in Taiwan turns out to be active, the investment management becomes very popular in the recent years. To facilitate the rapid development of information technology and the financial market, the application of information technology to financial investment becomes an important issue as essential evaluation metrics. In this thesis, we used a support vector regression machine for stock price in Taiwan, by inputting the data of daily and practical prices to implement approximate trend simulations and predictions. Then, we used the learned model data from the generated future stock price trends to analyze predictions and technical indices, and draw the trend diagram. Finally, we focus on modeling the business behavior of financial investment systems by the high-level fuzzy Petri net (HLFPN) for the purpose of developing an appropriate investment decision. Based on the HLFPN model, the proposed system provides individual investors to obtain relevant information to understand the investment trend. As a result, we proposed a practical financial investment system to enhance investment benefits and to help investors achieve the desired goals so as to improve the economy.
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