• 한국지반공학회논문집
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• 제16권6호
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• pp.127-139
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• 2000

In the study, an expert system was developed to predict the safety of tunnel and select proper tunnel reinforcement system using fuzzy quantification theory and fuzzy inference rule based on tunnel information database, For this development, many tunnelling sites were investigated and the applied countermeasures were studied after building tunnel database. There will be benefit for the deciding tunnel reinforcement method in the case of poor ground condition. The expert system developed in the study has two main parts, pre-module and post-module. Pre-module is used to decide input items of tunnel information based on the tunnel face mapping information which can be easily obtained in in-situ site. Then, using fuzzy quantification theory II, fuzzy membership function is composed and tunnel safety level is inferred through this membership function. Post-module is used to infer the applicability of each reinforcement methods according to the face level. The result of the predicted reinforcement system level was similar to measured ones. In-situ data were obtained in three tunnel sites including subway tunnel under Han River. Therefore, this system will be helpful to make the mose of in-situ data available and suggest proper applicability of tunnel reinforcement system to development more resonable tunnel support method without dependance of some experienced experts opinions.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제12권2호
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• pp.113-120
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• 2012

In this paper we study various properties of the fuzzy linear maps over the fuzzy quotient spaces. In particular we obtain some exact sequences of the fuzzy linear maps over the fuzzy quotient spaces.

• 제어로봇시스템학회논문지
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• 제15권8호
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• pp.786-791
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• 2009

Recently, digital camera module has been extensively utilized in mobile devices. The digital camera module should be smaller and lighter than digital still camera module to be used in mobile device. But, mobile camera can't get high quality image as good as the one of digital still camera due to the optical limitation of minimized module. Especially, AE system of mobile camera occurs excessive hunting and oscillation due to miniaturization of module. In this paper, improved AE algorithm which is applied fuzzy PI control is suggested to compensate this point.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.718-723
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• 1993

In this paper, we propose a neural network with fuzzy preprocessor not only for improving the classification accuracy but also for being able to classify objects whose attribute values do not have clear boundaries. The fuzzy input signal representation scheme is included as a preprocessing module. It transforms imprecise input in linguistic form and precisely stated numerical input into multidimensional numerical values. The transformed input is processed in the postprocessing module. The experimental results indicate the superiority of the backpropagation network with fuzzy preprocessor in comparison to the conventional backpropagation network.

• East Asian mathematical journal
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• 제28권1호
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• pp.1-11
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• 2012

In this paper, the concept of fuzzy soft module is introduced, some of their properties are discussed. Furthermore, the concept of fuzzy soft exactness is also given.

• 대한산업공학회지
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• 제26권4호
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• pp.306-314
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• 2000

In this paper we present a new approach to estimate link travel speed based on the hybrid neuro-fuzzy network. It combines the fuzzy ART algorithm for structure learning and the backpropagation algorithm for parameter adaptation. At first, the fuzzy ART algorithm partitions the input/output space using the training data set in order to construct initial neuro-fuzzy inference network. After the initial network topology is completed, a backpropagation learning scheme is applied to optimize parameters of fuzzy membership functions. An initial neuro-fuzzy network can be applicable to any other link where the probe car data are available. This can be realized by the network adaptation and add/modify module. In the network adaptation module, a CBR(Case-Based Reasoning) approach is used. Various experiments show that proposed methodology has better performance for estimating link travel speed comparing to the existing method.

• 한국지능시스템학회논문지
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• 제15권4호
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• pp.511-513
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• 2005

We investigate some situations in connection with two exact sequences of fuzzy linear maps.

• International Journal of Advanced Culture Technology
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• 제2권2호
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• pp.1-6
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• 2014

In this paper, we propose an intelligent streetlight system that has a complex sensor module of temperature, humidity, luminance and motion detection and controlled by the fuzzy logic based central monitoring system in order to get flexible and precise manipulation of the streetlight system in USN environment. The proposed streetlight system provides low power consumption and high efficiency by using sensed data from the complex sensor module, which were collected, processed, and analyzed by the fuzzy logic based central monitoring system. The performance of the proposed streetlight system is to be evaluated by a simulation study in terms of power savings and safety at the fields constructed as a test-bed under several suggested scenarios. Finally, we know that the proposed intelligent streetlight system can maximize the energy savings efficiently with the fuzzy logic based central monitoring system and selective remote dimming control by connecting it to the wireless ubiquitous sensor network (USN) using a Zigbee module.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.660-663
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• 2003

The advanced computer network technology enables connectivity of computers through an open network environment. There has been growing numbers of security threat to the networks. Therefore, it requires intrusion detection and prevention technologies. In this paper, we propose a network based intrusion detection model using Fuzzy Cognitive Maps(FCM) that can detect intrusion by the Denial of Service(DoS) attack detection method adopting the packet analyses. A DoS attack appears in the form of the Probe and Syn Flooding attack which is a typical example. The Sp flooding Preventer using Fuzzy cognitive maps(SPuF) model captures and analyzes the packet information to detect Syn flooding attack. Using the result of analysis of decision module, which utilized FCM, the decision module measures the degree of danger of the DoS and trains the response module to deal with attacks. The result of simulating the "KDD ′99 Competition Data Set" in the SPuF model shows that the Probe detection rates were over 97 percentages.

• 제어로봇시스템학회논문지
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• 제14권1호
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• pp.49-53
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• 2008

A fuzzy inference logic system is proposed for gas turbine engine fault isolation. The gas path measurements used for fault isolation are exhaust gas temperature, low and high rotor speed, and fuel flow. The fuzzy inference logic uses rules developed from a model of performance influence coefficients to isolate engine faults while accounting for uncertainty in gas path measurements. Inputs to the fuzzy inference logic system are measurement deviations of gas path parameters which are transferred directly from the ECM(Engine Control Monitoring) program and outputs are engine module faults. The proposed fuzzy inference logic system is tested using simulated data developed from the ECM trend plot reports and the results show that the proposed fuzzy inference logic system isolates module faults with high accuracy rate in the environment of high level of uncertainty.