• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.525-527
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• 1999

In this paper, we propose the target tracking system using fuzzy basis function expansion (FBFN) based on genetic algorithm (GA). In general, the objective of target tracking is to predict the future trajectory of the target based on the past position of the target obtained from the sensor. In the conventional and mathematical method, the parameter uncertainty and the environmental noise may deteriorate the performance of the system. To resolve these problems, we apply artificial intelligent technique to the tracking control of moving targets. The proposed method combines the advantages of both traditional and intelligent technique. The result of numerical simulation shows the effectiveness of the proposed method.

• Journal of Industrial Technology
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• v.29 no.B
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• pp.9-15
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• 2009

In the case of traditional binary encoding technique, it takes long time to converge the optimal solutions and brings about complexity of the systems due to encoding and decoding procedures. However, the ROGAs (real-coded genetic algorithms) do not require these procedures, and the k-means clustering algorithm can avoid global searching space. Thus, this paper proposes a new approach by using their advantages. The proposed method constructs the multiple predictors using the optimal differences that can reveal the patterns better and properties concealed in non-stationary time series where the k-means clustering algorithm is used for data classification to each predictor, then selects the best predictor. After selecting the best predictor, the cluster centers of the predictor are tuned finely via RCGKA in secondary tuning procedure. Therefore, performance of the predictor can be more enhanced. Finally, we verifies the prediction performance of the proposed system via simulating typical time series examples.

• Journal of Korean Association for Spatial Structures
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• v.16 no.4
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• pp.91-100
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• 2016

A retractable-roof spatial structure is frequently used for a stadium and sports hall. A retractable-roof spatial structure allows natural lighting, ventilation, optimal conditions for grass growth with opened roof. It can also protects users against various weather conditions and give optimal circumstances for different activities. Dynamic characteristics of a retractable-roof spatial structure is changed based on opened or closed roof condition. A tuned mass damper (TMD) is widely used to reduce seismic responses of a structure. When a TMD is properly tuned, its control performance is excellent. Opened or closed roof condition causes dynamic characteristics variation of a retractable-roof spatial structure resulting in off-tuning. This dynamic characteristics variation was investigated. Control performance of a passive TMD and a smart TMD were evaluated under off-tuning condition.

• Journal of Mechanical Science and Technology
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• v.17 no.2
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• pp.187-196
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• 2003

In this paper, a new methodology of evolutionary computations - An Adaptive Evolutionary Algorithm (AEA) is proposed. AEA uses a genetic algorithm (GA) and an evolution strategy (ES) in an adaptive manner in order to take merits of two different evolutionary computations : global search capability of GA and local search capability of ES. In the reproduction procedure, the proportions of the population by GA and ES are adaptively modulated according to the fitness. AEA is used to. designing fuzzy logic controller (FLC) for a high-angle-of-attack flight system for a super-maneuverable version of F-18 aircraft. AEA is used to determine the membership functions and scaling factors of an FLC. The computer simulation results show that the FLC has met both robustness and performance requirements.

• Journal of Sensor Science and Technology
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• v.20 no.3
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• pp.151-155
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• 2011

A variety of pattern recognition algorithms including neural networks may be applicable to the identification of odors. In this paper, an identification technique for an electronic odor sensing system applicable to wound state monitoring is presented. The performance of the radial basis function(RBF) network is highly dependent on the choice of centers and widths in basis function. For the fine tuning of centers and widths, those parameters are initialized by an ill-conditioned genetic fuzzy c-means algorithm, and the distribution of input patterns in the very first stage, the stochastic gradient(SG), is adapted. The adaptive RBF network with singular value decomposition(SVD), which provides additional adaptation capabilities to the RBF network, is used to process data from array-based gas sensors for early detection of wound infection in burn patients. The primary results indicate that infected patients can be distinguished from uninfected patients.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.428-429
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• 2008

In a previous paper, the distance relay algorithm for protecting of the underground power cable system was introduced. It effectively advance the errors using ACI(Advanced Computing Intelligence) technique. In this algorithm, the optimization was performed by fuzzy inference system and genetic algorithm. In this paper, hardware system based on ACI technique is introduced and tested by hardware test.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.2
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• pp.108-113
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• 2005

This paper suggests a control method for an efficient topology/parameter evolution in a bond graph-based GP design framework that automatically synthesizes designs for multi-domain, lumped parameter dynamic systems. We adopt a hierarchical breeding control mechanism with fitness-level-dependent differences to obtain better balancing of topology/parameter search - biased toward topological changes at low fitness levels, and toward parameter changes at high fitness levels. As a testbed for this approach in bond graph synthesis, an eigenvalue assignment problem, which is to find bond graph models exhibiting minimal distance errors from target sets of eigenvalues, was tested and showed improved performance for various sets of eigenvalues.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.2
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• pp.233-238
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• 2003

Living creatures maintain their variety through speciation, which helps them to have more fitness for an environment. So evolutionary algorithm based on biological evolution must maintain variety in order to adapt to its environment. In this paper, we utilize the concept of speciation. Each individual of population creates their offsprings using mutation, and next generation consists of them. Each individual explores search space determined by mutation. Useful search space is extended by differentiation, then population explorers whole search space very effectively. If evolvable hardware evolves through mutation, it is useful way to explorer search space because of less varying inner structure. We verify the effectiveness of the proposed method by applying it to two optimization problems.

• Science of Emotion and Sensibility
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• v.1 no.2
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• pp.93-103
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• 1998

효율적이고 체계적인 퍼지제어를 위해 조작자의 제어동작을 모델링하거나 공정을 모델링하는 기법이 필요하고, 또한 퍼지 추론시에 조건부의 기여도(contribution factor)의 결정과 동작부의 제어량의 결정이 추론의 결과에 중요하다. 본 논문에서는 추론시 조건부의 기여도와 동작부의 세어량이 퍼지 엔트로피의 개념하에서 수행되는 적응 퍼지 추론시스템을 제시한다. 제시된 시스템은 전방향 신경회로망의 토대위에서 구현되며 주건부의 기여도가 퍼지 엔트로피에 의하여 구해지고, 동작부의 제어량은 확장된 퍼지 엔트로피에 의하여 구해진다. 이를 위한 학습 알고리즘으로는 역전파 알고리즘을 이용하여 조건부의 파라미터의 동정을 하고 동작부 파라미터의 동정에는 국부해에 보다 강인한 유전자 알고리즘을 이용하다. 이러한 모델링 기법을 임펄스 잡음과 가우시안 잡음이 첨가된 영상에 적용하여 본 결과, 영상복원시에 발생되는 여러 가지의 경우에 대한 적응성이 보다 양호하게 유지되었고, 전체영상의 20%의 데이터만으로도 객관적 화질에 있어서 기존의 추론 방법에 비해 향상을 보였다.

• Journal of the Korea Institute of Building Construction
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• v.13 no.2
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• pp.159-168
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• 2013

Construction projects have become increasingly complex in recent years, resulting in substantial safety hazards and frequent fall accidents. In an attempt to prevent fall accidents, various safety management systems have been developed. These systems have mainly been evaluated qualitatively and subjectively by practitioners or supervisors, and there are few tools that can be used to quantitatively evaluate the performance of safety management systems. We propose an expertise-based safety performance evaluation model (EXSPEM), which integrates a fuzzy approach-based analytic hierarchy process and a regression approach. The proposed model uses S-shaped curves to represent the degree of contribution by subjective expertise and is verified by a genetic algorithm. To illustrate its practical application, EXSPEM was applied to evaluate the safety performance of a newly developed real-time mobile detector monitoring system. It is expected that this model will be a helpful tool for systematically evaluating the application of a robust safety control and management system in a complex construction environment.