Learning system operated through a layered neural network

Details Learning system operated through a layered neural network Learning system operated through a layered neural network

1995-05-08

1996-10-08

MacDonald, Allen R.

395 24, G06F 1518

Patent

active

055639836

ABSTRACT:
The present invention predicts an output result in response to unknown input data using a layered neural network. For example, learning data collected in time series with rate of changes included are learned through the layered neural network. As a result, a predicted value can be obtained with a smaller amount of learning data within a shorter learning time. The present invention comprises a rate of change calculating unit for calculating the rate of change of time-series data at two different time points, and a network generating unit for controlling the learning steps performed by the layered neural network using at least the rate of change of data as learning data so as to establish a neural network in which a weight value is determined for learning data. As a predicting system, it further comprises at least a neural network recognizing unit for applying to the neural network established by the network generating unit an output of the rate of change calculating unit outputted in response to input predicting data, and for obtaining a prediction result.

REFERENCES:
patent: 5109475 (1992-04-01), Kosaka et al.
Stock Market Prediction System with Modular NN Kimoto et al. IEEE 17-21 Jun. 1990.
Neural Sequential Associator and its Application to Stock Price Prediction Matsuba, IEEE 28 Oct.-1 Nov. 1991.
Using NN to predict several sequential and subsequent future values from time series data J. E. Bowen, IEEE/9-11 Oct. 1991.
Non-Linear System Diagnosis using NN and Fuzzy Logic Choi et al. IEEE International Conference on Fuzzy Systems Mar. 1992.

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