METHOD FOR CONSTITUTING NEURAL NETWORK AND LEARNING/ RECOLLECTING SYSTEM

Japanese Patent JP3214876

B2

PURPOSE: To optimize a sampling distance and a sampling time in the forecasting of time sequential data by evaluating the forecasting based upon a correlation coefficient between a measured pattern and a forecasted pattern.
CONSTITUTION: The number of input neurons corresponding to the sampling distance (d) and the sampling tithe (T) is previously and temporarily determined. Time sequential data formed by a teacher pattern forming means 1 are stored in teacher pattern memories 6, 7 and learning is executed by a learning means 4 based upon the stored contents of the memories 6, 7. After converging the learning, a forecasting accuracy evaluating means 3 calculates a correlation coefficient between a forecasted value based upon a neural network and a value corresponding to a teacher pattern. When the correlation coefficient satisfies required forecasting accuracy, a time sequential neural network having the distance (d) and the time (T) is determined by a time sequential neural network defining means 2. When the accuracy is not satisfied, at least one of the values (d), (T) is sequentially changed and the learning and the forecasting accuracy evaluation are repeated.

Minoru Koide
Haruki Inoue
Masakazu Yahiro
Noboru Abe

JP23997891A

October 02, 2001

September 19, 1991

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株式会社日立製作所
日立エンジニアリング株式会社

G05B13/02; G06F15/18; G06G7/60; G06N3/04; G06N3/08; G06N99/00; (IPC1-7): G06N3/04; G05B13/02; G06N3/08

JP4318656A
JP228701A

坪香、高田、脇田、「時系列処理機能をもつ階層型ニューラルネットワーク」電子情報通信学会技術研究報告、Ｖｏｌ．９１、Ｎｏ．９５（ＳＰ９１−６〜１７）、ｐｐ．６３〜７０（特許庁ＣＳＤＢ文献番号：ＣＳＮＴ１９９９００７３５００６）

Kazuko Tomita

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