Data processing: artificial intelligence – Knowledge processing system – Creation or modification
Patent
1997-07-11
1998-09-01
MacDonald, Allen R.
Data processing: artificial intelligence
Knowledge processing system
Creation or modification
G06F 1518
Patent
active
058025090
ABSTRACT:
A rule generation apparatus includes a label presenter in which when producing from training data including a set of specific values related to input and output variables rules representing input/output relationships between the input and output variables, numeric data of the training data is converted into categorical data expressed by symbols to generate an instance table, an RI device for extracting rules from the instance table, and a rule converter for converting the extracted rules into fuzzy rules. When the training data is divided to be distributively stored in a plurality of server processors, label assignment is conducted by each server processor such that a client processor later combines instance tables with each other to achieve rule induction and conversion.
REFERENCES:
patent: 5179634 (1993-01-01), Matsunaga et al.
patent: 5222197 (1993-06-01), Teng et al.
patent: 5229950 (1993-07-01), Niwa
patent: 5241620 (1993-08-01), Ruggiero
patent: 5295061 (1994-03-01), Katayama et al.
patent: 5422984 (1995-06-01), Iokibe et al.
patent: 5440672 (1995-08-01), Araki et al.
patent: 5504840 (1996-04-01), Hiji et al.
Kim et al., Automatic generation of membership function and fuzzy rule using inductive reasoning, IFIS 93, pp. 93-96, Dec. 3, 1993.
Silva et al., Induction of fuzzy production rules, Proceedings of the twentieth International symposium on multipe-valued logic, pp. 270-278, May 25, 1990.
Higgins et al., Learning fuzzy rule based neural network for function approximation, IJCNN, pp. 251-256, Jun. 11, 1992.
Higgins et al., Fuzzy rule -based networks for control, IEEE transactions on fuzzy systems, pp. 82-88, Feb. 1994.
Sebag et al., Learning membership functions from examples, IEEE computer society press, pp. 169-173, Apr. 28, 1993.
Krishnapuram et al., Compact fuzzy rule base generation methods for computer vision, Second IEEE International conference on fuzzy systems, pp. 809-814, vol. 2, Apr. 1, 1993.
Quinlan, J. Ross. "Learning Efficient Classification Procedures and Their Application to Chess End Games," Machine-Learning, Springer-Verlag, 1983, pp. 463-482 (English).
Hayashi, Isao, et al. "Learning Control of Inverted Pendulum System Using Artificial Neural Network Driven Fuzzy Reasoning," 5th Fuzzy Symposium, Jun. 2-3, 1989, pp. 183-188. (Japanese; English Abstract).
Enbutsu, Ichiro, et al. "Extractionof Explicit Knowledge From an Artificial Neural Network," IEEE Tokyo Section Denshi Tokyo, No. 30, 1991, pp. 101-104. (English).
Function of ES/TOOL/W-RI, Hitachi User Manual, 1990, pp. 33-53. (Japanese).
Maeda, Akira, et al. "A Fast Learning Algorithm for Fuzzy Membership Functions," 91-MIC-66-5, pp. 1-8. (Japanese; English Abstract).
Ashida Hitoshi
Hirai Chiaki
Ichimori Toshihide
Maeda Akira
Takahashi Yori
Hitachi , Ltd.
MacDonald Allen R.
Shah Sanjiv
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