• Journal of Information Processing Systems
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• 제16권5호
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• pp.1064-1073
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• 2020

The general situation of system composition and safety management of high-speed railway terminal is investigated and a comprehensive evaluation index system of operational security is established on the basis of railway laws and regulations and previous research results to evaluate the operational security management of the high-speed railway terminal objectively and scientifically. Index weight is determined by introducing interval eigenvalue method (IEM), which aims to reduce the dependence of judgment matrix on consistency test and improve judgment accuracy. Operational security status of a high-speed railway terminal in northwest China is analyzed using the traditional model of fuzzy comprehensive evaluation, and a general technique idea and references for the operational security evaluation of the high-speed railway terminal are provided. IEM is introduced to determine the weight of each index, overcomes shortcomings of traditional analytic hierarchy process (AHP) method, and improves the accuracy and scientificity of the comprehensive evaluation. Risk factors, such as terrorist attacks, bad weather, and building fires, are intentionally avoided in the selection of evaluation indicators due to the complexity of risk factors in the operation of high-speed railway passenger stations and limitation of the length of the paper. However, such risk factors should be considered in the follow-up studies.

• 정보처리학회논문지B
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• 제15B권6호
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• pp.603-608
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• 2008

본 논문에서는 주가의 일별 시가, 종가, 최고가, 최저가를 예측하기 위한 퍼지모델을 제안한다. 주가는 시장의 여러 경제 변수에 의존하므로 주가예측 모델의 입력변수를 선택하는 것은 쉽지 않은 일이다. 이와 관련하여 많은 연구가 있지만 정답이 있는 것은 아니다. 본 논문에서는 이를 해결하기 위해 주가 움직임 자체에 주목하는 스틱차트의 기술적 분석에 이용되는 정보를 퍼지규칙의 입력변수로 선택한다. 퍼지규칙은 사다리꼴 멤버쉽함수로 이루어진 전건부와 비선형 수식의 후건부로 구성된다. 최적의 퍼지규칙으로 구성된 퍼지모델을 찾아내기 위해 차분진화가 사용된다. 본 논문에 제안된 방법은 수치 예를 통해 다른 방법과의 비교로 타당성이 검토되며 KOSPI(KOrea composite Stock Price Index) 일별 데이터를 사용, 주가예측 퍼지모델을 구축하고 신경회로망 모델과 비교, 검토된다.

• 한국지능시스템학회논문지
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• 제14권1호
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• pp.52-56
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• 2004

주식시장에서 KOSPI200지수의 상승 또는 하락으로 분류 및 예측하는 정보는 선물 및 옵션시장에서 포토폴리오를 설계할 때 의사결정을 위해 중요한 기준이 된다. 경제지표인 시계열 패턴들의 향후 추세는 가장 최근의 경제패턴에 매우 종속적이기 때문에 최근의 패턴들을 가장 우선적으로 학습해야 할 필요가 있다. 본 논문에서는 시계열분석, 신경회로망, 그리고 다양한 분야에서 각광을 받고 있는 SVM(Support Vector Machine)과 Fuzzy SVM 모형의 분류 및 예측성능을 비교하였다. 특히 학습 DB에 따라 시계열성 속성을 갖는 퍼지소속함수에 가장 적합한 차원을 제시함으로서 Fuzzy SVM이 우수함을 입증하였다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2005년도 추계학술대회 학술발표 논문집 제15권 제2호
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• pp.205-208
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• 2005

We have fuzzy hypotheses testing from Bayesian statistics with ideas from fuzzy sets theory to generalize Bayesian methods both for samples of fuzzy data and for prior distributions with non-precise parameters. Appling the principle of agreement index, the posterior odds ratio in the favor of hypotheses $H_0$ is equal to product of the fuzzy odds ratio and the fuzzy likelihood ratio. If the Posterior odds ratio exceeds the grade judgement, we accept the hypothesis $H_0$ for the degree.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.238-242
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• 1991

This paper presents an approach to self-tuning PI control of dynamic plants, based on fuzzy logic application. A fuzzy logic composed of linguistic conditional statements is employed by defining the relations of input-output variables of the controller. In the synthesis of a fuzzy logic controller, one of the most difficult problem is the selection of linguistic control rules and parameters. To overcome this difficulty, self-tuning fuzzy PI controller (STFPIC) with a hierarchical structure in which the fuzzy PI controller is assigned as the lower level and the rule modification and parameter adjustment as the higher level. The rules and parameters are generated by the adjustment of membership function through performance index(PE). In this paper, the algorithm for of the controller performance is estimated by means of computer simulation.

• Journal of applied mathematics & informatics
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• 제26권5_6호
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• pp.861-876
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• 2008

This paper concerns a new method called Fuzzy Supervised Method for error matrix, the method has developed based on Adoptive Neuro- Fuzzy Inference Systems(ANFIS). For the performance point of view initially the new method tested with trial data and then this paper applies the proposed method with real world problems. So that this paper generated 1000 random error matrices in programming language [R] and then it tests the new proposed method for the error matrices. The results of Fuzzy Supervised Method given in terms of Kappa Index and Congalton Accuracy Indexes, and performance of Fuzzy Supervised Method has evaluated by using Pearson's test.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1996년도 추계학술대회 논문집
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• pp.439-443
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• 1996

A fuzzy teaming controller is experimentally designed to control the ball k beam system in this paper. Although most fuzzy controllers have been built just to emulate human decision-making behavior, it is necessary to construct the rule bases by using a learning method with self-improvement when it is difficult or impossible to get them only by expert's experience. The algorithm introduces a reference model to generate a desired output and minimizes a performance index function based on the error and error-rate using the gradient-decent method. In our balancing experiment of the ball ＆ beam system, this paper shows that the fuzzy control rules by learning are superior to the expert's experience.

• 산업경영시스템학회지
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• 제31권2호
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• pp.51-60
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• 2008

A solution method for fuzzy linear programs is proposed. A fuzzy linear program is converted to a crisp linear program with average indices being applied to the objective function and constraints. A comparative analysis between the proposed average index approach and the possibilistic approach is given. As an application example, the proposed method is applied to the linear programming model for fuzzy data envelopment analysis, and the result is compared with that of the possibilistic approach.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제3권1호
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• pp.7-12
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• 2003

In recent years, many attempts have been made to predict the behavior of bonds, currencies, stock or other economic markets. Most previous experiments used the neural network models for the stock market forecasting. The KOSPI 200 (Korea Composite Stock Price Index 200) is modeled by using different neural networks and fuzzy logic. In this paper, the neural network, the dynamic polynomial neural network (DPNN) and the fuzzy logic employed for the prediction of the KOSPI 200. The prediction results are compared by the root mean squared error (RMSE) and scatter plot, respectively. The results show that the performance of the fuzzy system is little bit worse than that of the DPNN but better than that of the neural network. We can develop the desired fuzzy system by optimization methods.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2000년도 춘계학술대회 학술발표 논문집
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• pp.114-117
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• 2000

In this paper, Fuzzy Self-organizing Neural Networks(FSONN) based on Fuzzy Neural Networks(FNN) is proposed to overcome some problems, such as the conflict between ovefitting and good generation, and low reliability. The proposed FSONN consists of FNN and SONN. Here, FNN is used as the premise part of FSONN and SONN is the consequnt part of FSONN. The FUN plays the preceding role of FSONN. For the fuzzy reasoning and learning method in FNN, Simplified fuzzy reasoning and backpropagation learning rule are utilized. The number of layers and the number of nodes in each layers of SONN that is based on the GMDH method are not predetermined, unlike in the case of the popular multi layer perceptron structure and can be generated. Also the partial descriptions of nodes can use various forms such as linear, modified quadratic, cubic, high-order polynomial and so on. In this paper, the optimal design procedure of the proposed FSONN is shown in each step and performance index related to approximation and generalization capabilities of model is evaluated and also discussed.