• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.9
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• pp.2265-2271
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• 1994

With the improvement of standard of living, requirement for comfortable and quiet environment has been increased and, therefore, there has been a many researches for active noise reduction to overcome the limit of passive control method. In this study, active noise control is performed in a duct system using intelligent control technique which needs not decide the coefficients of high order filter and the mathematical modeling of a system. Back propagation algorithm is applied as an intelligent control technique and control system is organized to exclude the error microphone and high speed operational device which are indispensable for conventional active noise control techniques. Furthermore, learning is performed by organizing acoustic feedback model, and the effect of the proposed control technique is verified via computer simulation and experiment of active noise control in a duct system.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.3
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• pp.64-73
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• 2011

This paper presents an algorithm for tracking lanes on the road based on corner detection techniques. The proposed algorithm shows high accuracy regardless of lane divider types, eg, solid line, dashed line, etc, and thus is of advantage to city streets and local roads where various types of lane dividers are used. A set of experiments was conducted on real roads with various types of lane dividers and results show an extract ratio over 87% in average.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.513-516
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• 2002

In electrical impedance tomography(EIT), various image reconstruction algorithms have been used in order to compute the internal resistivity distribution of the unknown object with its electric potential data at the boundary. Mathematically the EIT image reconstruction algorithm is a nonlinear ill-posed inverse problem. This paper presents two intelligent optimization algorithm techniques such as genetic algorithm and simulated annealing for the solution of the static EIT inverse problem. We summarize the simulation results for the three algorithm forms: modified Newton-Raphson, genetic algorithm, and simulated annealing.

• Journal of the Korean Institute of Intelligent Systems
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• v.3 no.2
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• pp.45-57
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• 1993

In this paper, we design the speed controller with high accuracy of an induction motor by the Fuzzy algorithms, which recently is invoking the remarkable interest. In order to reduce the steady state errors and the reaching times, the adjustment techniques of a series of optimal scaling factors are presented. Comparing with conventional PID control, the usefulness of proposed Fuzzy control will be proved by the simulations.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.05a
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• pp.193-196
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• 2003

최근 증가하고 있는 해상충돌사고는 대부분 선박을 조종하는 인간의 습관이나 실수에 기인하고 있다. 이를 해결하기 위한 방안으로 선박의 자율화 및 지능화의 연구가 활발히 진행되고 있는데 대표적인 연구로 지능형 자율운항제어시스템이 있다 지능형 자유운항제어시스템은 항로계획, 항로감시 및 충돌회피와 같은 전문가의 지식을 전산화한 것으로써 실제 선박에 장착되거나 시뮬레이션이 이루어질 때 시스템정보의 효과적인 전달을 위한 시각적 표현이 필요하다. 본 연구에서는 지능형 자율운항제어시스템의 2D기반 그래픽환경 구축을 위한 디스플레이를 개발한다. 디스플레이는 가상세계로부터 입력되는 데이터를 가상이미지로 변환한 후 사용자가 원하는 정보를 표현한다. 지능형 자율운항제어시스템에 근거한 디스플레이는 선박의 항해장비와 직접 연동되지 않기 때문에 구현, 수정 및 확장이 용이하다는 장점이 있다. 또한 본 연구에서 개발된 디스플레이는 가상이미지라는 개념을 도입하여 편리한 출력 수정과 선택이 가능하다. 제안된 연구는 가상세계의 데이터와 디스플레이에 표현된 정보를 비교ㆍ평가하여 성능을 검증한다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.2
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• pp.102-107
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• 2005

This paper presents the comparison and performance analysis for CPL and CMOS based designs. We have developed the Verilog-HDL codes for the proposed designs and simulated them using ModelSim for verifying the logical correctness and the timing properties of the proposed designs. The proposed designs are then analyzed at the layout level using LASI. The layouts of the proposed designs are simulated in Winspice for timing and power characteristics. The result shows that the new circuits presented consistently consume less power than the conventional design of the same circuits. It can also be seen that these circuits have the lesser propagation delay and thus higher speed than the conventional designs.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.3
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• pp.174-178
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• 2002

This paper discusses a blind equalization technique for FIR channel system, that might be minimum phase or not, in digital communication. The proposed techniques consist of two parts. One is to estimate the original channel coefficients based on fourth-order cumulants of the channel output, the other is to employ RBF neural network to model an inverse system fur the original channel. Here, the estimated channel is used as a reference system to train the RBF. The proposed RBF equalizer provides fast and easy teaming, due to the structural efficiency and excellent recognition-capability of R3F neural network. Throughout the simulation studies, it was found that the proposed blind RBF equalizer performed favorably better than the blind MLP equalizer, while requiring the relatively smaller computation steps in tranining.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.3
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• pp.210-214
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• 2002

Association rule mining is an exploratory learning task to discover some hidden dependency relationships among items in transaction data. Quantitative association rules denote association rules with both categorical and quantitative attributes. There have been several works on quantitative association rule mining such as the application of fuzzy techniques to quantitative association rule mining, the generalized association rule mining for quantitative association rules, and importance weight incorporation into association rule mining fer taking into account the users interest. This paper introduces a new method for generalized fuzzy quantitative association rule mining with importance weights. The method uses fuzzy concept hierarchies fer categorical attributes and generalization hierarchies of fuzzy linguistic terms fur quantitative attributes. It enables the users to flexibly perform the association rule mining by controlling the generalization levels for attributes and the importance weights f3r attributes.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.3
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• pp.363-370
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• 2009

In order to populate ontology, this paper presents a generalization method of ontology instances, extracted from texts and web pages, by using unsupervised learning techniques for word sense disambiguation, which uses open APIs and lexical resources such as Google and WordNet. According to the experimental results, our method achieved a 15.8% improvement over the previous research.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.290-293
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• 1996

This paper proposes a scheme of initial cluster center selection in FCM algorithm using the genetic algorithms. The FCM algorithm often fails in the search for global optimum because it is local search techniques that search for the optimum by using hill-climbing procedures. To solve this problem, we search for a hypersphere encircling each clusters whose parameters are estimated by the genetic algorithms. Then instead of a randomized initialization for fuzzy partition matrix in FCM algorithm, we initialize each cluster center by the center of a searched hypersphere. Our experimental results show that the proposed initializing scheme has higher probabilities of finding the global or near global optimal solutions than the traditional FCM algorithm.