• Journal of the Korean Society for Precision Engineering
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• v.13 no.4
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• pp.75-86
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• 1996

In this paper, we propose a new fuzzy-neural network control scheme for the speed and azimuth control of a mobile robot. The proposed control scheme uses a gaussian function as a unit function in the fuzzy-neural network, and back propagation algorithm to train the fuzzy-neural network controller in the frame-work of the specialized learning architecture. It is proposed a learning controller consisting of two fuzzy-neural networks based on independent reasoning and a connection net woth fixed weights to simply the fuzzy-neural network. The effectiveness of the proposed controller is illustrated by performing the computer simulation for a circular trajectory tracking of a mobile robot driven by two independent wheels.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.11a
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• pp.112-115
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• 2007

본 논문은 퍼지추론을 통해 개체의 유사성과 적합도의 종합적 평가를 이용한 유전알고리즘의 선태연산자를 제안한다. 단일 집단을 가상적으로 임의의 n 개의 개체군을 나누고, 개체의 적합도와 유사도에 기반한 퍼지추론을 통해, 효율적인 계층화를 구성하고자 한다. 동시에 점진형(steady-state) 진화방식과 결합시켜 계층화된 군집내에서 개체들이 조기에 수렴하는 현상을 방지해 줄 수 있도록 하고, 적은 개체를 이용하여 효율적인 진화가 가능하도록 구현하였다. 2가지 기만적 문제에 대해서 다른 선태 연산자들의 결과와 비교하였으며, 만족할만한 성능을 얻었다.

• 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 Intelligent Systems
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• v.11 no.6
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• pp.558-562
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• 2001

In this paper, a fuzzy hyperresolution principle called CFHR. Compensatory Fuzzy Hyperresolution, with positive compensation facility is proposed. Usually hyperresolution has several terms of conditon parts. Theser terms have to be connected by the an connective. If the main/max operator to be used the and operation, there is some dependency problem of the min/max operator. So , we propose a compensatory operator EGM and applied it to the CFHR, We show the CFHR does more meaningful reasoning than existing method. We also prove the completeness of CFHR.

• Knowledge Management Research
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• v.1 no.1
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• pp.81-90
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• 2000

This study proposes the knowledge discovery process for the effective mining of knowledge on the web. The proposed knowledge discovery process uses the Prior knowledge base and the Prior knowledge management system to reflect tacit knowledge in addition to explicit knowledge. The prior knowledge management system constructs the prior knowledge base using a fuzzy cognitive map, and defines information to be extracted from the web. In addition, it transforms the extracted information into the form being handled in mining process. Experiments using case-based reasoning and neural network" are performed to verify the usefulness of the proposed model. The experimental results are encouraging and prove the usefulness of the proposed model.

• Proceedings of the Korean Geotechical Society Conference
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• 2000.11a
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• pp.737-744
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• 2000

This paper resorts to rock mass rating and rock mass quality to draw value based on the evaluation of rock and to draw interrelation formula in relation to rock mass quality, A comparative analysis was given of survey values reported in the existing documents. This paper has tried to find out the relationship between RMR and Q System for the sake of choosing rational reinforcing patterns and of the safety of tunnels. The results run as follow: RMR=8.251n(Q)+43.83. This paper has also tried to find out the relationship between RMR and Q System by using Fuzzy Approximate Reasoning Concept. We suggest that those in charge should not depend on a single system only after evaluating the classification of rocks, and compare one result with another for the good of keeping track of the condition of base rocks in a better way.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1992.10a
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• pp.121-125
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• 1992

Grinding is considered as a very effective machining technology to attain the good surface quality of a components. However, the grinding operation still needs the skill and experience of an operator because of a lack of scientific and engineering principles. Therefore, recent development focus on expert systems which deal with domain specific knowledge in order to solve this problem. This paper describes an expert system for selecting the optimism grinding wheel by using the fuzzy reasoning and operation conditions in grinding. By the system unskilled workers will be able to make use of the knowledge and experience of skilled workers. The system is consist of programs that, (1) selection of the best wheel form among avairable wheel by using fuzzy reasoning, (2) determine wheel depth of cut, feed and wheel speed for grinding, work speed, and dressing condition. The developed system perform in using the CLIPS as a software tool and run under the IBM PC/AT as a hardware tool.

• International Journal of Internet, Broadcasting and Communication
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• v.6 no.2
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• pp.20-24
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• 2014

These days the large-scale car accidents have often been occurred by overspeeding in disregard of sharp curve, foggy and freezing regions. This paper has proposed the algorithm to calculate the safety speed in real time that can protect the car accidents under these weather and road conditions using Fuzzy reasoning theory. Under raining and snowing, drivers have to slow down the traffic safety speed by 1/3 of the traffic safety speed indicated on the existing speed sign plate based on their decision. So it is difficult to calculate and then observe the safety speed. This paper has performed the simulation that provides the deivers with the optimal safety speed considering the road and weather conditions in real time to improve these problems. We have proved this method can improve more 25% than the existing one.

• Journal of the Korean Institute of Navigation
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• v.20 no.3
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• pp.65-71
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• 1996

Recently, the Track Control System which was separated from the Course Control System so-called Auto-Pilot has been developed for track-keeping in coastal area. From this year, the NAV Sub-committee in IMO commenced to consider the Performance Standard for the Track Control System vigorously. This system will be integrated with ECDIS and IBS so that captain/officers should analysis ship's motion characteristics accurately in the route planning using the electronic nautical charts. In this paper, a new Route Analysis Algorithm using fuzzy reasoning in route planning was proposed for 2, 700 TEU container ship. In order to verify the track-keeping, the author established a ship mathematical model and executed the simulation of the Route Analysis Algorithm at on-line condition with Pentium PC. The results of ship trajectories of the Route Analysis Algorithm were found to be effective to get track control automatically.

• Journal of the Korea Society of Computer and Information
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• v.19 no.5
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• pp.11-18
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• 2014

In this paper, we propose a self-diagnosis system that is based on the ART2 algorithm in order to extract more detailed disease information by fuzzy reasoning method especially when the boundary of perceived symptoms are not clearly classified into disease categories. With that modification from previous version of the self health pre-diagnosis system, the proposed one is verified as more effective by field experts' evaluation as an intelligent assistant tool for public users before they consult with medical experts.