• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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• pp.118-121
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• 1998

In this paper, we propose another paradigm(QNBP) to be capable of overcoming Limitations of the traditional backpropagation(SDBP). QNBPis based on the method of Quasi -Newton(variable metric) with the nomalized direction vectors and computes step size through the linear search. Simulation results showed that QNBP was definitely superior to both the stochasitc SDBP and the deterministic SDBP in terms of accuracy and rate of convergence and might sumount the problem of local minima. and there was no different between DFP+SR1 and BFGS+SR1 combined algrothms in QNBP.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권4호
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• pp.626-648
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• 2011

Energy consumption of wireless access networks is in permanent increase, which necessitates development of more energy-efficient network management approaches. Such management schemes must result with adaptation of network energy consumption in accordance with daily variations in user activity. In this paper, we consider possible energy savings of wireless local area networks (WLANs) through development of a few integer linear programming (ILP) models. Effectiveness of ILP models providing energy-efficient management of network resources have been tested on several WLAN instances of different sizes. To cope with the problem of high computational time characteristic for some ILP models, we further develop several heuristic algorithms that are based on greedy methods and local search. Although heuristics obtains somewhat higher results of energy consumption in comparison with the ones of corresponding ILP models, heuristic algorithms ensures minimization of network energy consumption in an amount of time that is acceptable for practical implementations. This confirms that network management algorithms will play a significant role in practical realization of future energy-efficient network management systems.

• Geomechanics and Engineering
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• 제8권1호
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• pp.97-111
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• 2015

The kinematical approach of limit analysis is used to estimate the three dimensional stability analysis of rock slopes with nonlinear Hoek-Brown criterion under earthquake forces. The generalized tangential technique is introduced, which makes limit analysis apply to rock slope problem possible. This technique formulates the three dimensional stability problem as a classical nonlinear programming problem. A nonlinear programming algorithm is coded to search for the least upper bound solution. To prove the validity of the present approach, static stability factors are compared with the previous solutions, using a linear failure criterion. Three dimensional seismic and static stability factors are calculated for rock slopes. Numerical results of indicate that the factors increase with the ratio of slope width and height, and are presented for practical use in rock engineering.

• 한국정밀공학회지
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• 제21권10호
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• pp.137-146
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• 2004

This is the second of two companion papers concerned with the analysis and design of a pneumatic vibration isolation system. The properties of the system are clarified by observation of the transmissibility surface calculated by the models and algorithm developed in the first paper of this research. It Is shown that the nonlinear model proposed in this research is more closer to experimental results than the linear model that have been used in previous studies. The design optimization of the major design variables that affect the performance of the system is achieved by using the condition for attenuation, disturbance rejection and maximum damping in resonance peak. The design space search method is adopted for the optimization of the orifice area. The models, transmissibility calculation algorithms and design optimization techniques developed in this research are shown to be greatly helpful to the optimal design of the pneumatic vibration isolation system by experiment.

• 대한기계학회논문집B
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• 제24권6호
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• pp.845-851
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• 2000

In this paper, we show the numerical and the experimental results of two-dimensional fluid motions inside a rectangular container subjected to a background rotation added by a rotational oscillation. In the PlY experiment we apply a new algorithm, new three step search(NTSS), to the velocity calculation. In the numerical computation, the linear Ekman-pumping model was used to take the bottom friction effect into account. It was found that it well produces the experimental results at low e number.

• Advances in Computational Design
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• 제1권4호
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• pp.315-327
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• 2016

Damage detection and localisation in structures is essential since it can be a means for preventive maintenance of those structures under service conditions. The use of structural modal data for detecting the damage is one of the most efficient methods. This paper presents comparative performance of various state-of-the-art meta-heuristics for use in structural damage detection based on changes in modal data. The metaheuristics include differential evolution (DE), artificial bee colony algorithm (ABC), real-code ant colony optimisation (ACOR), charged system search (ChSS), league championship algorithm (LCA), simulated annealing (SA), particle swarm optimisation (PSO), evolution strategies (ES), teaching-learning-based optimisation (TLBO), adaptive differential evolution (JADE), evolution strategy with covariance matrix adaptation (CMAES), success-history based adaptive differential evolution (SHADE) and SHADE with linear population size reduction (L-SHADE). Three truss structures are used to pose several test problems for structural damage detection. The meta-heuristics are then used to solve the test problems treated as optimisation problems. Comparative performance is carried out where the statistically best algorithms are identified.

• 대한전기학회논문지:시스템및제어부문D
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• 제52권7호
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• pp.424-433
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• 2003

Evolutionary design related to the optimal design of Polynomial Neural Networks (PNNs) structure for model identification of complex and nonlinear system is studied in this paper. The PNN structure is consisted of layers and nodes like conventional neural networks but is not fixed and can be changable according to the system environments. three types of polynomials such as linear, quadratic, and modified quadratic is used in each node that is connected with various kinds of multi-variable inputs. Inputs and order of polynomials in each node are very important element for the performance of model. In most cases these factors are decided by the background information and trial and error of designer. For the high reliability and good performance of the PNN, the factors must be decided according to a logical and systematic way. In the paper evolutionary algorithm is applied to choose the optimal input variables and order. Evolutionary (genetic) algorithm is a random search optimization technique. The evolved PNN with optimally chosen input variables and order is not fixed in advance but becomes fully optimized automatically during the identification process. Gas furnace and pH neutralization processes are used in conventional PNN version are modeled. It shows that the designed PNN architecture with evolutionary structure optimization can produce the model with higher accuracy than previous PNN and other works.

• 대한전기학회논문지:전기물성ㆍ응용부문C
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• 제52권7호
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• pp.424-424
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• 2003

Evolutionary design related to the optimal design of Polynomial Neural Networks (PNNs) structure for model identification of complex and nonlinear system is studied in this paper. The PNN structure is consisted of layers and nodes like conventional neural networks but is not fixed and can be changable according to the system environments. three types of polynomials such as linear, quadratic, and modified quadratic is used in each node that is connected with various kinds of multi-variable inputs. Inputs and order of polynomials in each node are very important element for the performance of model. In most cases these factors are decided by the background information and trial and error of designer. For the high reliability and good performance of the PNN, the factors must be decided according to a logical and systematic way. In the paper evolutionary algorithm is applied to choose the optimal input variables and order. Evolutionary (genetic) algorithm is a random search optimization technique. The evolved PNN with optimally chosen input variables and order is not fixed in advance but becomes fully optimized automatically during the identification process. Gas furnace and pH neutralization processes are used in conventional PNN version are modeled. It shows that the designed PNN architecture with evolutionary structure optimization can produce the model with higher accuracy than previous PNN and other works.

• 우주기술과 응용
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• 제2권2호
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• pp.67-80
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• 2022

최근의 우주개발기술 선진국들은 우주의 평화적 이용이라는 보편적 가치를 넘어서 자국의 이익을 극대화하기 위한 발판으로 우주의 전략적 활용에 더욱 더 집중하고 있으며, 조기경보 위성과 같이 지상에서 발사된 화염 정보를 이용하여 우주로 발사된 발사체의 실시간 감시와 궤적 추적 기능 등을 담당하는 위성들을 지속적으로 개발해 오고 있다. 본 연구에서는 이러한 조기경보 위성에서 발사체의 궤적을 실시간으로 추정할 수 있는 알고리즘을 진화연산이라는 인공지능 기법을 적용하여 제안하고, 이러한 비행 궤적 추정 알고리즘을 비행 궤적 추정 시스템의 시뮬레이터를 통하여 임의의 발사체 비행 궤적에 적용함으로써 제안된 방법의 성능과 특징을 입체적으로 확인하고자 한다.

• 한국인터넷방송통신학회논문지
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• 제24권3호
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• pp.103-108
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• 2024

가꾸로 퍼즐은 다항시간으로 퍼즐을 풀 수 있는 방법이 알려져 있지 않은 NP-완전 문제이다. 지금까지는 가능한 모든 경우수를 대입해 보는 전수탐색 법이나 선형계획법을 적용하고 있다. 본 논문은 박스 크기와 합 실마리에 따른 들어갈 수 없는 숫자들에 대한 규칙인 마법의 규칙을 찾아내었다. 마법의 규칙에 기반하여 빈 셀에 들어갈 수 없는 숫자들을 행과 열 합 실마리에 대한 박스에서 삭제하였다. 다음으로 합 실마리 값에 기반하여 박스에 들어갈 수 없는 숫자들을 삭제하였다. 최종적으로 단일 숫자만 존재하는 셀을 실마리로 확정하였다. 제안된 알고리즘을 7개의 벤치마킹 실험 데이터에 적용한 결과 모든 문제에 대해 해를 구할 수 있음을 보였다.