Inference rule determining method and inference device

Details Inference rule determining method and inference device Inference rule determining method and inference device

1995-10-13

2000-08-15

Downs, Robert W.

Data processing: artificial intelligence

Fuzzy logic hardware

Fuzzy neural network

706 6, 706900, 395 22, 395900, G05B 1300

Patent

active

RE0368237

ABSTRACT:
An inference rule determining process according to the present invention sequentially determines, using a learning function of a neural network model, a membership function representing a degree which the conditions of the IF part of each inference rule is satisfied when input data is received to thereby obtain an optimal inference result without using experience rules. The inventive inference device uses an inference rule of the type "IF . . . THEN . . ." and includes a membership value determiner (1) which includes all of IF part and has a neural network; individual inference quantity determiners (21)-(2r) which correspond to the respective THEN parts of the inference rules and determine the corresponding inference quantities for the inference rules; and a final inference quantity determiner which determines these inference quantities synthetically to obtain the final results of the inference. If the individual inference quantity determiners (2) each has a neural network structure, the non-linearity of the neural network models is used to obtain the result of the inference with high inference accuracy even if in object to be inferred is non-linear.

REFERENCES:
patent: 4730259 (1988-03-01), Gallant
patent: 4773099 (1988-09-01), Bokser
patent: 4837725 (1989-06-01), Yamakawa
"Fuzzy Modeling" Society of Instrument and Control Engineers Papers, vol. 23, No. 6, pp. 650-652, 1987; Gean-Taek Kang, Michio Sugeno.
"Revised GMDH Algorithm Estimating Degree of the Complete Polynomial", pp. 928-934, 1986.
D. E. Rumelhart, G.E. Hinton and R. J. Williams, "Learning Representations by Back-propergating Errors", Nature, vol. 323, pp. 523-536, Oct. 9, 1986.
Procyk et al., "A Linguistic Self-Organizing Controller", Automatica, v.15, pp. 15-30 Jan. 1979.
Hayashi et al., "Neural-Network-Driven Fuzzy Reasoning Model", Proc. 28.sup.th SICE Annul.Conf., Jul. 1989, 1343-1346.
Lippmann, R. P., "An Intro. to Computing with Neural Nets," IEEE ASSP Mag. Apr. 1987, 4-22.
Takagi et al., "Artificial Neural Network Driven Fuzzy Reasoning" Intl. Workshop on Fuzzy System Applications, Aug. 1988, 217-218.
Isao Hayashi, et al, "Formulation of Fuzzy Reasoning by Neural Network", 4th Fuzzy Symposium (Tokyo, May 30-31, 1988), pp. 55-60.
C.G. Looney, "Learning in Three-Plex Fuzzy Logic Networks," Proceedings of the ISMM International Symposium, XP000566865, Feb. 1-3, 1988, pp. 157-160.
J. Voevodsky, "Plato/Aristotle: A Neural Net Knowledge Processor," IEEE First International Conference on Neural Networks, XP002058597, Jun. 21-24, 1987, San Diego, CA, pp. 399-408.
L.C. Shiue and R.O. Grondin, "On Designing Fuzzy Learning Neural-Automata," IEEE First International Conference on Neural Networks, XP002058598, Jun. 21-24, 1987, San Diego, CA, pp. II-299 through 11-307.

Affiliated with

Also associated with

Rating

Inference rule determining method and inference device does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Inference rule determining method and inference device, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Inference rule determining method and inference device will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFUS-PAI-O-1994510