• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1574-1575
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• 2007

"Dynamic Neural Unit"(DNU) based upon the topology of a reverberating circuit in a neuronal pool of the central nervous system. In this thesis, we present a genetic DNU-control scheme for unknown nonlinear systems. Our methodis different from those using supervised learning algorithms, such as the backpropagation (BP) algorithm, that needs training information in each step. The contributions of this thesis are the new approach to constructing neural network architecture and its trainin.

• Industrial Engineering and Management Systems
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• v.3 no.2
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• pp.116-122
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• 2004

This paper presents a process plan selection model with multiple objectives. The process plans for all parts should be selected under multiple objective environment as follows: (1) minimizing the sum of machine processing and material handling time of all the parts considering realistic shop factors such as production volume, processing time, machine capacity, and capacity of transfer device. (2) balancing the load between machines. A multiple objective mathematical model is proposed and an evolutionary algorithm with the adaptive recombination strategy is developed to solve the model. To illustrate the efficiency of proposed approach, numerical examples are presented. The proposed approach is found to be effective in offering a set of satisfactory Pareto solutions within a satisfactory CPU time in a multiple objective environment.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.1
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• pp.53-58
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• 2002

In the construction of successful fuzzy models for nonlinear systems, the identification of an optimal fuzzy model system is an important and difficult problem. Traditionally, sGA(simple genetic algorithm) has been used to identify structures and parameters of fuzzy model because it has the ability to search the optimal solution somewhat globally. But SGA optimization process may be the reason of the premature local convergence when the appearance of the superior individual at the population evolution. Therefore, in this paper we propose a new method that can yield a successful fuzzy model using VmGA(virus messy genetic algorithms). The proposed method not only can be the countermeasure of premature convergence through the local information changed in population, but also has more effective and adaptive structure with respect to using changeable length string. In order to demonstrate the superiority and generality of the fuzzy modeling using VmGA, we finally applied the proposed fuzzy modeling methodof a complex nonlinear system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5592-5609
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• 2017

JPEG steganography detection is an active research topic in the field of information hiding due to the wide use of JPEG image in social network, image-sharing websites, and Internet communication, etc. In this paper, a new steganalysis method for content-adaptive JPEG steganography is proposed by integrating the evolutionary feature selection and classifier ensemble selection. First, the whole framework of the proposed steganalysis method is presented and then the characteristic of the proposed method is analyzed. Second, the feature selection method based on genetic algorithm is given and the implement process is described in detail. Third, the method of classifier ensemble selection is proposed based on Pareto evolutionary optimization. The experimental results indicate the proposed steganalysis method can achieve a competitive detection performance by compared with the state-of-the-art steganalysis methods when used for the detection of the latest content-adaptive JPEG steganography algorithms.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.844-846
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• 1998

In this study, an adaptive evolutionary computation(AEC), which uses adaptively a genetic algorithm having global searching capability and an evolution strategy having local searching capability with different methodologies, is suggested. This paper develops AEC for solving ELD problem with piecewise quadratic cost function. Numerical results show that the proposed AEC can provide accurate dispatch solutions within reasonable time for the ELD problem with piecewise quadratic cost function.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.1118-1120
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• 1998

In this study, an adaptive evolutionary computation (AEC), which uses adaptively a genetic algorithm having global searching capability and an evolution strategy having local searching capability with different methodologies, is suggested. We applied the AEC to design of fuzzy logic controllers for a PSS (power system stabilizer). FLCs for PSS controllers are designed for damping the low frequency oscillations caused by disturbances such as tile sudden changes of loads, outages in generators, transmission line faults, etc. The membership functions of FLCs is optimally determined by AEC.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2003.06a
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• pp.98-101
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• 2003

본 논문에서는, 패턴 인식시 데이타의 최적의 특성을 구성할 수 있는 새로운 신경망 구조인 적응적 트리맵을 제안한다. 유전 알고리즘을 사용한 적응적 트리맵(adaptive tree map ATM)은 데이터의 특징에 대한 중요도를 유전 알고리즘으로 구성하고, 특징의 우선 순위에 따라 트리구조를 도입하고 데이터의 유사성에 따라 신경망의 뉴런이 분리, 병합 될 수 있다. 패턴인식의 인식률에 영향을 미치는 인자 중에서 가장 중요한 특징은 연구자의 선택에 의하여 사용되거나 무시될 수 있으며, 반복적인 실험을 통하여 적절한 특징을 사용할 수 있으나 최적의 특징은 될 수 없다. 그러나 본 논문에서 제안한 ATM을 이용하면 블랙박스로 구성된 적응적인 시스템을 이용하여 원하는 출력을 얻을 수 있게 된다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.3
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• pp.1372-1377
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• 2013

In this Paper, a back propagation neural network learning algorithm based on the complex multilayer perceptron is represented for controling and detecting interference of the received signals in cellular mobile communication system. We proposed neural network adaptive correlator which has fast convergence rate and good performance with combining back propagation neural network and the receiver of cellular. We analyzed and proved that NNAC has lower bit error probability than that of traditional RAKE receiver through results of computer simulation in the presence of the tone and narrow-band interference and the co-channel interference.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.5
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• pp.139-145
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• 2018

An outrigger system is used widely to increase the lateral stiffness of high-rise buildings, resulting in reduced dynamic responses to seismic or wind loads. Because the dynamic characteristics of earthquake or wind loads are quite different, a smart vibration control system associated with an outrigger system can be used effectively for both seismic and wind excitation. In this study, an adaptive smart structural control system based on an outrigger damper system was investigated for the response reduction of multi-hazards, including seismic and wind loads. A MR damper was employed to develop the smart outrigger damper system. Three cities in the U.S., L.A., Charleston, and Anchorage, were used to generate multi-hazard earthquake and wind loads. Parametric studies on the MR damper capacity were performed to investigate the optimal design of the smart outrigger damper system. A smart control algorithm was developed using a fuzzy controller optimized by a genetic algorithm. The analytical results showed that an adaptive smart structural control system based on an outrigger damper system can provide good control performance for multi-hazards of earthquake and wind loads.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.5
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• pp.45-50
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• 1998

This paper presents the process generating the 3-dimensional free f o r m hull form by using an ASMOD(Adaptive Spline Modeling of Observation Data) and a hybrid curve approximation. For example, we apply an ASMOD to the generation of a SAC(Sectiona1 Area Curve) in an initial hull form design. That is, we define SACS of real ships as B-spline curves by a hybrid curve approximation (which is the combination method of a B-spline fitting method and a genetic algorithm) and accumulate a database of control points. Then we let ASMOD learn from the correlation of principal dimensions with control points and make the ASMOD model for SAC generation. Identically, we apply an ASMOD to the generation of other hull form characteristic curves - design waterline curve, bottom tangent line, center profile line. Conclus~onally we can generate a design hull form from these hull form characteristic curves.