• Journal of Institute of Control, Robotics and Systems
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• v.3 no.2
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• pp.204-213
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• 1997

In this paper, an application of fuzzy-neuron reasoning to the control of an activated sludge plant is presented. The activated sludge process is widely used in modern wastewater treatment plants. The operation control of the activated sludge process, however, is difficult due to the following reasons : 1)The complexity of the wastewater components, 2)the change of the wastewater influent, and 3)the adjustment errors in the control process. Because of these reasons, it is difficult to obtain mathematical model that really reflect the relationship between the variables and parameters in the process of wastewater treatment correctively and effectively. In this paper, the activated sludge process(A.S.P.) is modeled by a new fuzzy-neuron network representing nonlinear characteristics. These fuzzy-neurons have fuzzy rules with complementary membership function. Based on the constructed model, graphic simulator on X-window system as a graphic integrated environment is implemented. The efficacy of the proposed control scheme was evaluated and demonstrated by means of the field test.

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2432-2434
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• 2004

In this paper, we present a novel approach for the structure of Fuzzy Neural Network(FNN) based on wavelet function and apply this network structure to the solution of the tracking problem for mobile robots. Generally, the wavelet fuzzy model(WFM) has the advantage of the wavelet transform by constituting fuzzy basis function(FBF) and the conclusion part to equalize the linear combination of FBF with the linear combination of wavelet functions. However, it is very difficult to identify the fuzzy rules and to tune the membership functions of the fuzzy reasoning mechanism. Neural networks, on the other hand, utilize their learning capability for automatic identification and tuning. Therefore, we design a wavelet based FNN structure(WFNN) that merges these advantages of neural network, fuzzy model and wavelet. To verify the efficiency of our network structure, we evaluate the tracking performance for mobile robot and compare it with those of the FNN and the WFM.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.5
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• pp.69-79
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• 2014

This paper proposes the Collision Prevention System based on Fuzzy which reasons a risk with the location information of vehicles and pedestrians and prevents collision between vehicles, and between a vehicle and a pedestrian with the reasoned risk. The proposed system provides three functions. First, it identifies a pedestrian's location with his smart phone and a vehicle's location with the GPS equipped in the vehicle. and transfers the identified information to their neighbors. Second, it makes a vehicle and a pedestrian reason a risk by considering a moving direction, a moving speed and road information. Third, it provides a vehicle and a pedestrian with the reasoned information such as route detour, speed reduction, etc. Therefore, the proposed collision prevention system based on Fuzzy not only prevents collision accidents beforehand by reasoning a risk, but also reduces a variety of losses by protecting traffic accident and congestion.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.11
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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.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.22 no.3
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• pp.644-653
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• 1998

In resistance spot weld, the assurance of weld quality has been a long-standing problem. Since the weld nuggets if resustance spot welding form between the workpieces, visual detection of defects in usually impossible. Welding quality of resistance spot welding can be verified by non destructive and destructive inspections such as X-Ray inspection and testing of weld strength. But these tests, in addition to being time-consuming and costly, can entail risks due to sampling basis. The purpose of this study is the development of the monitoring system based on fuzzy inference, aimed at diagonosis of quality in resistance spot welding. The fuzzy inference system consists of fuzzy input variables, fuzzy membership functions and fuzzy rules. For inferring the welding quality(strength), the experimental data of the spot welding were acquired in various welding conditions with the monitoring system designed. Some fuzzy input variables-maximum, slop and difference values of electrode movement signals-were extracted from the experimental data. It was confirmed that the fuzzy inference values of strength have a .${\pm}$5% error in comparison with actual values for the selected welding conditions(9-10.5KA, 10-14 cycle, 250-300 $kg_f$). This monitoring system can be useful in improving the quality assurance and reliability of the resistance spot welding process.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.5
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• pp.197-202
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• 2014

It is used the important method that Oriental doctor determines patient's disease status observing patient's state of tongue in Oriental medicine clinic. In this paper, it developed the how to use the pulse diagnosis and tongue diagnosis based on s mart based electronic acupuncture. It will do objective judgment without wrong diagnosis. In this paper, we developed the algorithm that it automatically determines patient health condition and smart electronic acupuncture kit using fuzzy logic and fuzzy reasoning system were completed. In this paper, Simulation results proved that acupuncture is effective than the traditional method of using electronic intelligence.

• Journal of the Society of Naval Architects of Korea
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• v.32 no.4
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• pp.136-141
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• 1995

Determination and optimization of proper welding condition are very important tasks to be directly related to weld quality and productivity. On this research the relationship between welding parameters and results is investigated systematically. Theoretical method, statistical analysis of experimental data and analysis of empirical knowledge are applied for this work. These results are represented by empirical equations, fuzzy rules and artificial intelligent knowledge forms in the knowledge base. The approximate reasoning of fuzzy expert system and the information in the knowledge base are used for recommendation of suitable welding condition, and optimization of welding parameter which is based on the evaluation of welding results by user.

• Korea Information Processing Society Review
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• v.11 no.6
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• pp.56-75
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• 2004

In this article we address some system characteristics and challenging issues in developing Context-aware Middleware for Ubiquitous Computing. The functionalities of a Context-aware Middleware includes gathering context data from hardware/software sensors, reasoning and inferring high-level context data, and disseminating/delivering appropriate context data to interested applications/services. The Middleware should facilitate the query, aggregation, and discovery for the contexts, as well as facilities to specify their privacy policy. Following a formal context model using ontology would enable syntactic and semantic interoperability, and knowledge sharing between different domains. Moddleware should also provide different kinds of context classification mechanical as pluggable modules, including rules written in different types of logic (first order logic, description logic, temporal/spatial logic, fuzzy logic, etc.) as well as machine-learning mechanical (supervised and unsupervised classifiers). Different mechanisms have different power, expressiveness and decidability properties, and system developers can choose the appropriate mechanism that best meets the reasoning requirements of each context. And finally, to promote the context-trigger actions in application level, it is important to provide a uniform and platform-independent interface for applications to express their need for different context data without knowing how that data is acquired. The action could involve adapting to the new environment, notifying the user, communicating with another device to exchange information, or performing any other task.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.2
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• pp.244-251
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• 2007

Intention reading technique is essential to provide personalized services toward more convenient and human-friendly services in complex ubiquitous environment such as a smart home. If a system has knowledge about an user's intention of his/her behavioral pattern, the system can provide mote qualified and satisfactory services automatically in advance to the user's explicit command. In this sense, learning capability is considered as a key function for the intention reading technique in view of knowledge discovery. In this paper, ore introduce a personalized media control method for a possible application iii a smart home. Note that data pattern such as human behavior contains lots of inconsistent data due to limitation of feature extraction and insufficiently available features, where separable data groups are intermingled with inseparable data groups. To deal with such a data pattern, we introduce an effective engineering approach with the combination of fuzzy logic and probabilistic reasoning. The proposed learning system, which is based on IFCS (Iterative Fuzzy Clustering with Supervision) algorithm, extract probabilistic fuzzy rules effectively from the given numerical training data pattern. Furthermore, an extended architectural design methodology of the learning system incorporating with the IFCS algorithm are introduced. Finally, experimental results of the media contents recommendation system are given to show the effectiveness of the proposed system.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.576-578
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• 1999

본 논문에서는 생물학적인 DNA와 유전자 알고리즘의 진화 메커니즘에 근거를 둔 DNA 코딩방법을 변형하여 새로운 DNA 코딩 방법을 제안한다. 이 방법은 기존의 DNA 코딩 방법이 DNA 유전자의 Redundancy와 Over-lapping 성질 때문에 갖고 있는 DNA 자체의 특성인 염색체의 길이를 자유자재로 변화시킬 수 있는 코딩 기술에 진화단계에서 변형을 가할 수 있는 새로운 유전자 알고리즘을 추가하여, 초기에 국소해로 접근하는 일반적인 유전자 알고리즘의 위험 부담률을 줄이고, 전역 해로의 접근 가능성을 높이는 방법을 제시한다. 또한. 이 변형된 DNA 코딩 방법의 가능성을 입증하기 위하여 시스템 제어에 필요한 지식을 표현하는 적당한 퍼지 규칙을 후건부의 매개변수의 동조만을 통하여 획득하고, 이 규칙에 변형된 DNA 코딩 방법을 적용하여 최적화 된 새로운 퍼지규칙 획득 알고리즘을 개발한다. 제안된 알고리즘을 이용한 퍼지 제어기를 설계하고. 이 제어기의 유용성을 입증하기 위하여 병렬형 이중 도립진자 시스템에 적용하여 시뮬레이션을 실행한 결과 효과적으로 퍼지규칙을 획득하고 제어함을 알 수 있다.