• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.11
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• pp.103-110
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• 1990

This paper studies on an on-line recognition of handwritten Hangeul characters using the fuzzy inference. To solve the ambiguity due to the variations of writing style by writes, these handwri-tten characters are recognized by means of the fuzzy inference on the production rule which is generated with every relative position information between strokes. In order to reduce the processing time, a subgroup which is previously classified with the number of strokes of reference characters is selected according to the number of strokes of input character, and the tolerance limit of distances between input character and reference characters of a subgroup is introduced to reduce the reference characters which is applied to the fuzzy inference. Experimental results for handwritten Hanguel charters 3990 by 10 writers show the recognition rate of $99.5{\%}$and the average processing time of 0.4sec/character.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.4
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• pp.346-360
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• 1992

This paper proposed a method of identity decision of moving object by the fuzzy inference. Moving object is extracted by the difference picture method and identity decision parameters of moving object are chosen area, perimeter. A/p ratio and vertex. In the brightness variation of 600 Lux-1600Lux, we determined the maximum error often parameters and then generated a fuzzified data. Fuzzified data are generated from the reference image and then decided the identity of extracted parameter by the fuzzy inference using fuzzy production rule. In order to verify validity of proposed method, experiment are performed with a toy car. As a result, it was shown that decision error was less than 4%

• The Journal of the Korea Contents Association
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• v.9 no.6
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• pp.45-52
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• 2009

Recently, we started a project development of the digital expert system for the product design supporting in manufacturing industry. This digital expert system is used to the engineers in manufacturing industry for the process control, production management and system management. In this paper, we develop the ontology based inference engine shell for building of expert system. This expert system shell included a various functions which of Korean language supporting, graphical ontology map modeling interface, fuzzy rule definition function and etc. And, we introduce the knowledge representation method for the ontology map building and ontology based fuzzy inferencing method.

• IE interfaces
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• v.13 no.1
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• pp.92-99
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• 2000

Conflicts and interruptions caused by resource failures and rush orders require a nonlinear dynamic production management. Generally the PP&C systems used in industry presently do not meet these requirements because of their rigid concepts. Starting with the grasp of the disadvantages of current approaches, this paper presents a control structure that enables system to react to various malfunctions using a planning tolerance concept. Also, production processes are modeled by using Fuzzy-Petri-Net modeling tool in other to handle the complexity of job allocation and the existence of many disparities. On the basis of this model the developed system support the short-term shop control by rule based decision.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.132-137
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• 1993

In this paper, a fish drying process control system is proposed, which predicts the proper change with time in weight of the material fish and the drying conditions in advance, based on the performance of skilled worker. In order to implement a human expertise into an automated fish drying process control system, an experimental analysis is made and a model for the process is built. The proposed system divided into two procedures: The procedure before drying and the one during drying. The procedure before drying is for the prediction of necessary drying time. To estimate the necessary drying time, first, the proper change in weight for the product is obtained by using fuzzy reasoning. The condition part of the production rule consists of the factors of fish body and the expected degree of dryness. Kext, the necessary drying time is obtained by regression models. The variables employed in the models are the factors, inferred change in weight and drying conditions. The model for the procedure during drying is also proposed for more accurate estimation, which is described by a system of linear-differential equations.