• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.3
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• pp.505-513
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• 2009

Z. Cao had proposed NFRM(new fuzzy reasoning method) which infers in detail using relation matrix. In spite of the small inference rules, it shows good performance than mamdani's fuzzy inference method. But the most of fuzzy systems are difficult to make fuzzy inference rules in the case of MIMO system. The past days, We had proposed the MIMO fuzzy inference which had extended a Z. Cao's fuzzy inference to handle MIMO system. But many times and effort needed to determine the relation matrix elements of MIMO fuzzy inference by heuristic and trial and error method in order to improve inference performances. In this paper, we propose a MIMO fuzzy inference method with the learning ability witch is used a gradient descent method in order to improve the performances. Through the computer simulation studies for the inverse kinematics problem of 2-axis robot, we show that proposed inference method using a gradient descent method has good performances.

• Journal of the Korean Society for Library and Information Science
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• v.14
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• pp.3-18
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• 1987

The factors which can help the library users trace the specific subject that she or he needs are most important, when they are not sure of what they need exactly in front of a classified catalogue. This study is about what the factors are and how the factors affect the inference of users' reasoning structure. Since the classified catalogues are reflected by the classification structure, naturally the logic in the classification system becomes the focus of the study. This study concludes the classification system which enables the library users to use their reasoning capabilities, viz. the classification system which can help the users trace the specific subject even as they are not sure of the exact subject they need has following factors in the system. 1. It should have the validity based on the facts in the components of the classification system. 2. It should be logically arranged when the components of the classification system are placed in due sequence. 3. The notation of the system should be based on mnemonics. The reason is that the indispensable factors in the formation of inference of human reasoning structure are: 1. the premises which are based on the facts and 2. the logical relationship between the premises and conclusions which are induced from the premises.

• Proceedings of the KIEE Conference
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• 1990.07a
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• pp.167-170
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• 1990

This paper presents a preliminary study of introduction of the Dempster-Shafer inexact reasoning method to the expert system for the power system design problem. A brief review of Dempster-Shafer theory of evidence is presented and development of an inference engine adopting the Dempster-Sharer theory is reported. Developed inference engine has a ability of handling both the confirming and disconfirming knowledge represented in the production rule, and has a general purpose application in the design and diagnosis problems. Its applicability has been tested on the problem of the protection scheme selection, one of the typical design problem and we believe, it has shown the feasibility of adoption of the inexact reasoning methodology into the design problem.

• Journal of KIISE:Software and Applications
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• v.26 no.11
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• pp.1324-1331
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• 1999

물체의 공간에서의 운동을 다루는 공간 추론의 연구에서 충돌을 이해하는 것은 중요하다. 본 논문에서는 정성적 충돌 이론과 추론 기법을 소개하고자 한다. 충돌 해석에 있어 관련된 물체의 공간적 속성과 운동방향의 상호작용을 분석하여 충돌로 인한 힘과 운동 방향의 전달을 계산하였다. 추론 과정에 있어서는 충돌이 갖는 특성인 불연속적인 변화에 대한 분석과 회전 운동으로 인한 변화의 분석이 소개되었다. 제안된 충돌 이론과 추론 기법은 구현되어 자동차 충돌 사고의 충돌에 적용되어 유효성을 입증할 수 있었다. Abstract Understanding collision is important in spatial reasoning problems that study the motions of objects. This paper introduces qualitative collision theory and reasoning techniques. Force and motion transfers are computed by analyzing the interactions of the spatial properties and motions of the objects. This paper also presents inference techniques for handling discontinuous changes and angular changes by rotation. These theories and inference techniques are implemented and applied to real car-to-car collision accidents. The test results verify the reliabilities of our techniques.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.9
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• pp.1095-1103
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• 1992

An approach to fuse the fuzzy inference system which is able to deal with imprecise and uncertain information and genetic algorithms which display the excellent robustness in complex optimization problems is presented in this paper. In order to combine genetic algorithms and fuzzy inference engine effectively the new reasoning method is suggested. The efficient identification method of fuzzy rules is proposed through the adjustment of search areas of genetic algorithms. The feasibilty of the proposed approach is evaluated through simulation.

• The Transactions of the Korea Information Processing Society
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• v.4 no.4
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• pp.1025-1034
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• 1997

Inference process of resolution-based automated reasoning easily consumes the memory of computer without giving any useful result by priducing lots of fruioless information which are not necessary for the conslusion. This paper suggests a control strategy for saving the space of computer memory and reducing the inference time. The strategy uses a restriction that comparatively irrelevant axioms do mot take pare in the resoluition. In order to analyze and determine the priorities of the input axioms of joning the inference process, the system employs the fuzzy relational products.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.10
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• pp.98-105
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• 1997

In this work, we proesent a bidirectional approximate reasoning method and fuzzy inference network for interval valued decision making systems. For this, we propose a new type of similarity measure between two fuzzy vectors based on the Ordered Weighted Averaging (OWA) operator. Since the proposed similarity measure has a structure to give the extreme values by choosing a suitable weighting vector of the OWA operator, it can render an interval valued similarity value. From this property, we derive a bidirectional approximate reasoning method based on the similarity measure and show its fuzzy inference network implementation for the decision making systems requiring the interval valued decisions.

• Journal of the Korean Data and Information Science Society
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• v.15 no.3
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• pp.663-675
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• 2004

A battlefield simulation is the evaluation and analysis of the battlefield area, based on the data for terrain, climate, unit's maneuver and tactics basically required in battlefield simulation. Because it is difficult for the military authorities to collect all of the information perfectly for the reason of communication technology, jamming, and tactics, the military authorities need the future moving status for the target units by using acquired moving information. Therefore, we propose a moving object management system that concurrently provides domain reasoning function for the battlefield simulation. In order to implement the proposed system, we show the data modeling of the moving object for the battlefield simulation, and propose an inference engine using domain rule base and spatiotemporal operation. Also, we analyze the query response rate by inference function to verify domain reasoning of the implemented system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1274-1276
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• 1993

We have designed a multiple-valued fuzzy Approximate Analogical-Reseaning system (AARS). The system uses a similarity measure of fuzzy sets and a threshold of similarity ST to determine whether a rule should be fired, with a Modification Function inferred from the Similarity Measure to deduce a consequent. Multiple-valued basic fuzzy blocks are used to construct the system. A description of the system is presented to illustrate the operation of the schema. The results of simulations show that the system can perform about 3.5 x 106 inferences per second. Finally, we compare the system with Yamakawa's chip which is based on the Compositional Rule of Inference (CRI) with Mamdani's implication.

• Journal of the Korean Society of Systems Engineering
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• v.18 no.1
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• pp.84-89
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• 2022

For system maintenance optimization, it is necessary to establish a state information system by CBM+ including CBM and RCM, and sensor selection for CBM+ application requires system process for function model analysis at the early design stage. The study investigated the contents of CBM and CBM+, analyzed the function analysis tasks and procedures of the system, and thus presented a D-FMEA based sensor selection inference methodology at the early stage of design for CBM+ application, and established it as a D-FMEA based sensor selection inference process. The D-FMEA-based sensor inference methodology and procedure in the early design stage were presented for diesel engine sub assembly.