• 제목/요약/키워드: Intelligent Techniques

검색결과 972건 처리시간 0.025초

Evolutionary Approach for Traveling Salesperson Problem with Precedence Constraints

  • 문치웅;윤영수
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2007년도 춘계학술대회 학술발표 논문집 제17권 제1호
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    • pp.305-308
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    • 2007
  • In this paper we suggest an efficient evolutionary approach based on topological sort techniques for precedence constrained TSPs. The determination of optimal sequence has much to offer to downstream project management and opens up new opportunities for supply chains and logistics. Experimental results show that the suggested approach is a good alternative to locate optimal solution for complicated precedence constrained sequencing as in optimization method for instance.

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지능형 전원설비의 원격관리제어기 개발에 관한 연구 (A Study on Development of Remote Management Controller for Intelligent Power Equipment)

  • 임병국
    • 한국산업융합학회 논문집
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    • 제9권1호
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    • pp.79-86
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    • 2006
  • In this study, we research and develope Intelligent Remote management controller. According to the load condition, we will apply various control techniques and plan high efficient Demand control. After development, According to the Demand Control, An electricity enterprisers will expect enlargement of equipment coefficient, elevation of back up load factor and reduction effect of equipment investment. On Customer side, They will expect reduction of electric fee, saving energy and variety of service choice.

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Support Vector Machine을 이용한 지능형 신용평가시스템 개발 (Development of Intelligent Credit Rating System using Support Vector Machines)

  • 김경재
    • 한국정보통신학회논문지
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    • 제9권7호
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    • pp.1569-1574
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    • 2005
  • In this paper, I propose an intelligent credit rating system using a bankruptcy prediction model based on support vector machines (SVMs). SVMs are promising methods because they use a risk function consisting of the empirical error and a regularized term which is derived from the structural risk minimization principle. This study examines the feasibility of applying SVM in Predicting corporate bankruptcies by comparing it with other data mining techniques. In addition. this study presents architecture and prototype of intelligeht credit rating systems based on SVM models.

LMI를 이용한 GBSB 신경망 설계 (Design of GBSB Neural Networks Using LMI)

  • 조혁;박주영;박대희
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 1997년도 추계학술대회 학술발표 논문집
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    • pp.409-412
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    • 1997
  • In this paper, we propose a novel synthesis method of GBSB(Generalized BSB)-based neural autoassociative memories in which we analyze qualitative properties of GBSB model, recast a design problem of an associative memory to LMIP(Linear Matrix Inequality Problem), and optimize the LMIP using LMI techniques. The obtained memory satisfies many of the required properties of associative memories and has some peculiar properties. Comparing experimental results with those of others, we show its correctness and effectiveness.

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A New Class of Similarity Measures for Fuzzy Sets

  • Omran Saleh;Hassaballah M.
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제6권2호
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    • pp.100-104
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    • 2006
  • Fuzzy techniques can be applied in many domains of computer vision community. The definition of an adequate similarity measure for measuring the similarity between fuzzy sets is of great importance in the field of image processing, image retrieval and pattern recognition. This paper proposes a new class of the similarity measures. The properties, sensitivity and effectiveness of the proposed measures are investigated and tested on real data. Experimental results show that these similarity measures can provide a useful way for measuring the similarity between fuzzy sets.

영상 이해를 통한 지능형 영상압축 시스템 (An Intelligence Image Compression System through Image Understanding)

  • Kim, Jin-Hyung
    • 대한전자공학회논문지
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    • 제24권6호
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    • pp.961-968
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    • 1987
  • This paper describes an intelligent image compression system called AIIC which is capable of adjusting image compression ratios ranging from 1:1 to 12,000:1 depending on available bandwidth. This system utilizes not only conventional image compression algorithms but also intelligent techniques through understanding image contents to achieve ultra-high compression ratios. This system was simulated on a micro-computer network.

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An Artificial Intelligent algorithm for an autonomous Cleaning Robot

  • Hyun, Woong-Keun
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 1999년도 하계종합학술대회 논문집
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    • pp.800-804
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    • 1999
  • An intelligent path planning algorithm for an autonomous cleaning robot is presented. This algorithm recognizes obstacle on the architectural CAD draft and generates subgoals as tracking points which executes the area filling task based on heuristic approach. A sweeping path is planned by sequentially connecting the tracking points in such a way that (1) the connected line segments should be crossed, (2) the total tracking points should be as short as possible, (3) the tracking line should not pass through the obstacle. Feasibility of the developed techniques has been demonstrated on real architectural CAD draft.

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General problem solver를 이용한 intelligent LP 모형화에 대한 연구

  • 박성주;권오병
    • 한국경영과학회:학술대회논문집
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    • 대한산업공학회/한국경영과학회 1991년도 춘계공동학술대회 발표논문 및 초록집; 전북대학교, 전주; 26-27 Apr. 1991
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    • pp.469-474
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    • 1991
  • Recent interests in intelligent LP modeling aim to support MS/OR-naive users to be able to apply LP models to practical problems without the expert knowledges required. For more generalized LP modeling, a GPS(General Problem Solver)-based approach is suggested in this paper. It identifies modeling process as a means-ends analysis process. In view of this approach, a) we first divide the knowledges into domain specific assertive knowledges(state) and procedural knowledges about LP modeling(operator and macro) for model-domain independence, b) and then generate LP model according to the difference resolution techniques.

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전기자동차의 조향과 추진을 위한 지능형 통합 제어 시스템 (An intelligent integrated control system for steering and traction of electric vehicles)

  • 서일홍;박명관
    • 전자공학회논문지B
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    • 제33B권7호
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    • pp.21-31
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    • 1996
  • An intelligent integrated control system is designed for the active steering and the left/right traction force distribution control of electric vehicles, where input-output linearization is employed. Also, a fuzzy-rule-based cornering force estimator is suggested to avoid using an uncertain highly nonlinear expression, and a neural network compensator is additively utilized for the estimator to correctly find cornering forece. With these techniques, the proposed control system is shown by simulation results to be robust against drastic change of the external environments such as road conditions.

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