Economic phenomenon predicting and analyzing system using neural

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395 23, 395 24, 364402, G06F 1518

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active

054448190

ABSTRACT:
An economic phenomenon predicting and/or analyzing system using a neural network. In the disclosed system, time series data indicating economic phenomena are input to preparation modules, and moving-average values and their differences are generated. One of the preparation modules performs a predetermined process over the time series data indicating an economic phenomenon, i.e. the change of TOPIX, to remove trends. A pattern sorter sorts the trend-free data into a certain number of groups. Average values of various time series data, their differences and the result of pattern sorting are input to input layer neurons of the network. The network is provided in advance with learning information of the change of TOPIX in the past. The output of the output layer neurons will be a value of prediction of the change of TOPIX. For the output of hidden layer neurons, principal components are obtained by principal analysis modules. A correlation analysis module obtains a distribution of frequency of principal component rankings and analyzes the correlation between the explanation variants and the output of the neural network based on the obtained distribution of frequency.

REFERENCES:
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patent: 5109475 (1992-04-01), Kosaka et al.
patent: 5140523 (1992-08-01), Frankel et al.
An Intelligent Trend Prediction and Reversal Recognition System Using Dual-Module Neural Networks Gia-Shuh Jang IEEE/ 9-11 Oct. 1991.
Stock Market Prediction System with Modular Neural Networks T. Kimoto et al., IEEE/ 17-21 Jun. 1990.
A 3D Neural Net for Business Forecasting F. S. Wong IEEE/ 8-1 Jan. 1991.
TME Series Prediction by Adaptive Networks: A Dynamical Systems Perspective D. Lowe et al., IEEE/ Feb. 1991.
Commodity Trading with a Two Year Old Collard, IEEE Jul. 1991.
IEEE "IJCNN International Joint Conference on Neural Networks" Vol. 1 Jun. 1990.

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