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Based on the data warehouse stock trading data analysis and prediction of

Author: ShiZhiBin
Tutor: ChenLiChao
School: North China Institute of Technology
Course: Applied Computer Technology
Keywords: Data warehouse Stock Forecasting Neural Networks
CLC: TP311.13
Type: Master's thesis
Year: 2002
Downloads: 359
Quote: 1
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Abstract


This paper analyzes China 's stock market analysis forecasting methods situation at home and abroad data warehouse and data mining technology widely used in various fields to provide stock investment decisions for the purpose of research data warehouse technology applied to the stock analysis system , the establishment of sub - oriented listening, decision-oriented data platform, using data mining technology in the feed-forward neural network prediction of time series analysis methods, analyzes and forecasts on the stock data to supplement the shortcomings of the existing technical analysis . The main contents are as follows: (1 ) the data warehouse and data mining technology and its application are discussed . And stock analysis method of comprehensive analysis, pointed out that the lack of prediction method based on the feed-forward neural network ; (2 ) in accordance with the data warehouse construction method , stock analysis system needs analysis , data conversion particle size divided , split operation to achieve the establishment of data warehouse stock analysis system initially established , in addition to general inquiries , statistics , analysis and decision - making platform ; (3) of the multilayer structure of the fiber network to God -BP algorithm and back-propagation algorithm , the general establishment of feedforward neural networks for time-series data to predict the network model and forecast design method based on BP network actual forecast stock data , the results show that: when the sample data (including input data and target data ) is normalized , the prediction accuracy was significantly higher than the traditional method ; (4) the factors that affect the network generalization are discussed , and analyze stock data processing sub- stock trend forecasting, can improve the generalization capability of the network , the results show that the prediction accuracy is significantly improved .

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