• 한국지능시스템학회논문지
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• 제12권3호
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• pp.231-238
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• 2002

진화퍼지모델링은 퍼지추론시스템과 진화연산의 장점을 결합한 모델링 방법으로써 전역근사최적화를 수행한다. 본 논문에서는 진화퍼지모델링의 가장 중요한 과정 중 하나인 퍼지규칙의 생성방법으로써 퍼지클러스터링을 제안한다. 퍼지클러스터링을 실험 혹은 시뮬레이션의 결과에 적용함으로써, 비선형성이 강하고 복잡한 설계문제를 적절하게 묘사할 수 있는 퍼지 규칙을 생성할 수 있다. 퍼지클러스터링의 결과로 얻어지는 클러스터에 대한 실험치의 소속정도를 활용하여 진화퍼지모델링의 효율을 향상시킬 수 있다. 제안된 방법의 유효성을 검증하기 위해 실제 자동차 내장재에 설계문제를 선정하여 전역근사화를 수행하였다. 클러스터 수와 퍼지규칙의 선택과 관련하여 여러 다양한 경우에 대해서 진화퍼지모델링을 수행하여 그 결과를 비교하였고 이를 통하여 제안된 방법이 시스템을 묘사하는 적절한 퍼지규칙을 생성하고 모델링의 오차를 만족할 만한 수준으로 유지하면서 계산시간을 줄일 수 있음을 확인하였다.

• 산업공학
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• 제15권4호
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• pp.338-348
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• 2002

In this paper, we present a restricted tabu search(RTS) algorithm that schedules jobs on identical parallel machines in order to minimize the maximum lateness of jobs. Jobs have release times and due dates. Also, sequence-dependent setup times exist between jobs. The RTS algorithm consists of two main parts. The first part is the MATCS(Modified Apparent Tardiness Cost with Setups) rule that provides an efficient initial schedule for the RTS. The second part is a search heuristic that employs a restricted neighborhood generation scheme with the elimination of non-efficient job moves in finding the best neighborhood schedule. The search heuristic reduces the tabu search effort greatly while obtaining the final schedules of good quality. The experimental results show that the proposed algorithm gives better solutions quickly than the existing heuristic algorithms such as the RHP(Rolling Horizon Procedure) heuristic, the basic tabu search, and simulated annealing.

• Journal of information and communication convergence engineering
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• 제6권2호
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• pp.222-227
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• 2008

The important problem in designing a Fuzzy Logic Controller(FLC) is generation of fuzzy control rules and it is usually the case that they are given by human experts of the problem domain. However, it is difficult to find an well-trained expert to any given problem. In this paper, I describes an application of genetic algorithm, a well-known global search algorithm to automatic generation of fuzzy control rules for FLC design. Fuzzy rules are automatically generated by evolving initially given fuzzy rules and membership functions associated fuzzy linguistic terms. Using genetic algorithm efficient fuzzy rules can be generated without any prior knowledge about the domain problem. In addition expert knowledge can be easily incorporated into rule generation for performance enhancement. We experimented genetic algorithm with a non-trivial vehicle controling problem. Our experimental results showed that genetic algorithm is efficient for designing any complex control system and the resulting system is robust.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 추계학술대회 논문집 전력기술부문
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• pp.21-23
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• 2006

As a general rule for evaluating dependability of a system, reliability is commonly considered which barely rays attention to the system behavior, however the estimation is based on the assumption of a fault-frost system, which may be impracticable and inaccurate especially for complicated system. This paper introduces a security and dependability integrated approach to analyze the availability of a fault-active system both from dependability and security points of view. Two fault modes involved are discussed about the impairment to the system reliance. The approach can be well applied to estimate and quantify the attribute of system robustness with the help of Markov chain process, which is good at solving status related problem. The comparison result between dual system and IEC61850-based almighty backup system is shown to sup-port the suggested approach.

• 전기학회논문지
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• 제57권4호
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• pp.551-559
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• 2008

Increase in power consumption can cause a serious stability problem of an electric power system without construction of new power plants or transmission lines. Also, it can generate large power loss of the system. In costly and environmentally effective manner to avoid constructing the new infrastructures such as power plants and transmission lines, etc, the distributed generation(DG) has paid great attentions so far as a solution for the above problem. Selection of optimal location and size of the DG is the necessary process to maintain the stability and reliability of existing system effectively. However, the systematic and cardinal rule for this issue is still open question. In this paper, the method to determine optimal location of the DG is proposed by considering power loss when the DG is connected to an electric power grid. Also, optimal size of not only the corresponding single DG but also the multi-DGs is determined with the proposed systematic approach. The IEEE benchmark 30-bus test system is analyzed to evaluate the feasibility and effectiveness of the proposed method.

• 한국멀티미디어학회논문지
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• 제22권6호
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• pp.665-675
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• 2019

In this paper, we compare and analyze the classification performance of deep learning algorithm Convolutional Neural Network(CNN) ac cording to ensemble generation and combining techniques. We used several CNN models(VGG16, VGG19, DenseNet121, DenseNet169, DenseNet201, ResNet18, ResNet34, ResNet50, ResNet101, ResNet152, GoogLeNet) to create 10 ensemble generation combinations and applied 6 combine techniques(average, weighted average, maximum, minimum, median, product) to the optimal combination. Experimental results, DenseNet169-VGG16-GoogLeNet combination in ensemble generation, and the product rule in ensemble combination showed the best performance. Based on this, it was concluded that ensemble in different models of high benchmarking scores is another way to get good results.

• Journal of the Korean Data and Information Science Society
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• 제23권5호
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• pp.939-948
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• 2012

데이터 마이닝 기법들 중에서 가장 많이 활용되고 있는 연관성 규칙은 방대한 데이터베이스에서 항목간의 관계를 흥미도 측도에 의해 명확히 수치화함으로써 그들간의 관련성을 표시해주는 기법이다. 양의 연관성 규칙 마이닝이 임의의 한 항목이 발생하면 다른 항목도 발생한다는 규칙을 생성하기 위한 기법인 반면에, 음의 연관성 규칙은 어느 항목이 발생하면 다른 항목은 발생하지 않는다는 규칙을 찾아내는 기법이다. 음의 연관성 규칙은 양의 연관성 규칙의 활용과 마찬가지로 고객의 구매 경향 및 마케팅 정책을 제시할 수 있고 교차판매와 매장 진열 등과 같이 타겟 마케팅에 활용 가능하다. 양의 연관성 규칙에 음의 연관성 규칙을 추가하게 되면 어떤 제품을 판매하기 위해서는 그 제품만 마케팅 하는 것뿐만 아니라 더 나아가 그 제품이 아닌 어느 제품을 마케팅 하는것이 필요한지를 판단할 수 있다. 본 논문에서는 기존의 음의 신뢰도의 단점을 보완할 수 있는 음의 기여 순수 신뢰도를 제안한 후, 이에 대해 흥미도 측도가 가져야 할 조건들을 조사하였으며, 예제 데이터를 활용하여 음의 기여 순수 신뢰도의 유용성을 고찰하였다.

• 산업경영시스템학회지
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• 제39권3호
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• pp.170-179
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• 2016

In this paper we have tackled the outstanding inventory planning problems over new product launching period in a more holistic manner by addressing first the definition of efficient business rules to effectively control and reduce the inventory risks followed by the rigorous explanations on the implementation guide on suggested inventory planning rules. It is not unusual for many companies in the consumer electronics market to make a great effort to reduce the time to launch a new product because the ability to bring out higher performing products in such a short time period greatly increases the probability for them to remain competitive in the high tech market. Among so many newly developed products, those products with new features and technologies appeal to many potential customers while products which fail to win customers by design and prices rapidly disappear in the market. To adapt to this business environment, those companies have been trying to find the answer to minimize the inventory of old products so they can move to next generation products quickly with less obsolete material. In the experimental implementation of our rule-based inventory planning, Company 'S' reduced the inventory cost for the outgoing products as low as 49% of its peak level of its preceding product version in just 5 month after the adoption of rule-based inventory planning process and system. This paper concluded the subject with a suggestion that the best performance of rule-based inventory planning is guaranteed not from one-time campaign of process improvement along with system development but the decision maker's continuing support and attention even without seeing any upcoming business crisis.

• 전자공학회논문지B
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• 제29B권11호
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• pp.120-129
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• 1992

In this paper we propose a fuzzy-neural network(FNN) which includes both advantages of the fuzzy logic and the neural network. The basic idea of the FNN is to realize the fuzzy rule-base and the process of reasoning by neural network and to make the corresponding parameters be expressed by the connection weights of neural network. After constructing the FNN, a novel controller consisting of a conventional P-controller and a FNN is explained. In this control scheme, the rule-base of a FNN are automatically generated by error back-propagation algorithm. Also the parallel connection of the P-controller and the FNN can guarantee the stability of a plant at initial stage before the rules are completely created. Finally the effectiveness of the proposed strategy will be verified by computer simulations using a 2 degree of freedom robot manipulator.

• International Journal of Control, Automation, and Systems
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• 제4권3호
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• pp.372-381
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• 2006

The purpose of this study was to develop a process management system to manage ingot fabrication and improve ingot quality. The ingot is the first manufactured material of wafers. Trace parameters were collected on-line but measurement parameters were measured by sampling inspection. The quality parameters were applied to evaluate the quality. Therefore, preprocessing was necessary to extract useful information from the quality data. First, statistical methods were used for data generation. Then, modeling was performed, using the generated data, to improve the performance of the models. The function of the models is to predict the quality corresponding to control parameters. Secondly, rule extraction was performed to find the relation between the production quality and control conditions. The extracted rules can give important information concerning how to handle the process correctly. The dynamic polynomial neural network (DPNN) and decision tree were applied for data modeling and rule extraction, respectively, from the ingot fabrication data.