• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.71.2-71
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• 2001

This paper deals with nonlinear system modelling using neural network and genetic algorithm. Application of neural network to control and identification is actively studied because of their approximating ability of nonlinear function. It is important to design the neural network with optimal structure for minimum error and fast response time. Genetic algorithm is getting more popular nowadays because of their simplicity and robustness. In this paper, We optimize neural network structure using genetic algorithm. The genetic algorithm uses binary coding for neural network structure and search for optimal neural network structure of minimum error and response time. Through extensive simulation, Optimal neural network structure is shown to be effective for ...

• 정보처리학회논문지C
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• 제14C권7호
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• pp.583-588
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• 2007

이동 애드 혹 네트워크는 기반 망의 도움 없이 모바일 노드의 자유로운 참여와 이탈에 의해 임시적인 네트워크를 구성하기 용이하다. 이러한 모바일 노드는 한정된 에너지에 의존한다. 그래서 무선 애드 혹 네트워크에서 에너지와 관련된 문제들이 중요한 연구과제로 다루어진다. 모바일 노드의 에너지 소비를 줄이기 위해 IEEE 802.11 PSM를 적용한 다중 홉 애드 혹 네트워크 모델에 대해서 최근 많은 연구가 이루어졌다. IEEE 802.11 PSM은 단일 홉 애드 혹을 가정하고 제안되었다. IEEE 802.11 PSM을 다중 홉 애드 혹 네트워크에 적용을 하게 될 경우 경로설정 메시지를 받지 못한 모바일 노드에 의해 우회하는 경로가 발생하게 된다. 우회하는 경로는 전송지연뿐만 아니라 모바일 노드의 에너지 소비를 증가시키게 된다. 본 논문에서는 경로 설정 메시지를 전송받지 못한 모바일 노드에 의해 발생하는 우회하는 경로를 최적의 경로로 재설정하는 알고리즘을 제안하였다. 모바일 노드는 자신의 송수신 범위에 있는 노드들의 데이터를 엿들을 수 있다. 무선 매체는 동일한 대역을 사용하는 모든 모바일 노드에 의해 공유되어진다. 이러한 매체의 특성을 이용하여 모든 모바일 노드들은 우회경로를 감시하고 우회경로가 발생하였을 경우 자신의 라우팅 테이블의 정보를 수정하거나 이웃한 모바일 노드에게 라우팅 업데이트 요청 메시지를 보내어 최적의 경로로 재설정하게 된다. 우회경로를 최적의 경로로 재설정함으로써 전송지연과 불필요한 에너지 소비를 줄일 수 있었다. 시뮬레이션을 통해 제안 알고리즘을 수행하기위한 오버헤드는 무시할 수 있을 정도로 작다는 것을 알 수 있었다.

• Water Engineering Research
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• 제1권1호
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• pp.63-74
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• 2000

This paper presents a two- phase search scheme for optimal pipe expansion of expansion of existing water distribution systems. In pipe network problems, link flows affect the total cost of the system because the link flows are not uniquely determined for various pipe diameters. The two-phase search scheme based on stochastic optimization scheme is suggested to determine the optimal link flows which make the optimal design of existing pipe network. A sample pipe network is employed to test the proposed method. Once the best tree network is obtained, the link flows are perturbed to find a near global optimum over the whole feasible region. It should be noted that in the perturbation stage the loop flows obtained form the sample existing network are employed as the initial loop flows of the proposed method. It has been also found that the relationship of cost-hydraulic gradient for pipe expansion of existing network affects the total cost of the sample network. The results show that the proposed method can yield a lower cost design than the conventional design method and that the proposed method can be efficiently used to design the pipe expansion of existing water distribution systems.

• 전기학회논문지
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• 제62권10호
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• pp.1451-1457
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• 2013

Recently, new concept of energy systems such as microgrid, smart grid, supergrid, and energy network has been introducing. In this paper, the concept of the centralized micro-energy network, which is an energy community of a building group without district heating system, is introduced. In addition, a mathematical model for optimal operation of the micro-energy network as a main function of an energy management system (EMS) for the micro-energy network is proposed. In order to show the validation, the proposed model is tested through the simulation and analyzed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권12호
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• pp.4389-4410
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• 2014

Network coding is a promising technology that increases system throughput by reducing the number of packet transmissions from the source node to the destination node in a saturated traffic scenario. Nevertheless, some packets can suffer from end-to-end delay, because of a queuing delay in an intermediate node waiting for other packets to be encoded with exclusive or (XOR). In this paper, we analyze the delay according to packet arrival rate and propose two network coding schemes, iXOR (Intelligent XOR) and oXOR (Optimal XOR) with Markov Decision Process (MDP). They reduce the average delay, even under an unsaturated traffic load, through the Holding-${\chi}$ strategy. In particular, we are interested in the unsaturated network scenario. The unsaturated network is more practical because, in a real wireless network, nodes do not always have packets waiting to be sent. Through analysis and extensive simulations, we show that iXOR and oXOR are better than the Distributed Coordination Function (DCF) without XOR (the general forwarding scheme) and XOR with DCF with respect to average delay as well as delivery ratio.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1997년도 춘계학술대회 학술발표 논문집
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• pp.271-274
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• 1997

This paper presents the optimization technique for design of a CMAC network by using an evolution strategies(ES). The proposed technique is designed to find the optimal parameters of a CMAC network, which can minimize the learning error between the desired output and the CMAC network's as well as the number of memory used in the CMAC network. Computer simulations demonstrate the effectiveness of the proposed design method.

• 한국산림과학회지
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• 제84권1호
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• pp.63-70
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• 1995

이 논문에서는 neural network기법에 의해 소규모 임분의 시업계획을 분석하는 방법과 적용성을 평가하였다. 이를 위해서 적정한 임분시업체계를 계산하기 위한 neural network 모델을 개발하고, neural network의 구조체계와 network을 교육시키기 위해 요구되는 자료량의 측면에서 적용성을 검토하였다. 연구목적상 모델의 교육 및 비교분석에 요구되는 적정 시업체계에 대한 자료는 기존의 비선형 시업체계분석모델을 이용하였다. 이 시업체계 분석모델은 동령급 구조의 긴잎 소나무(Pinus palustris) 단순림의 적정시업체계를 분석하는 모델로서 전림수확생장함수에 의해 임분의 생장이 예측되는 모델이다. neural network 모델의 적용성 검토에 요구되는 분석자료들은 이 비선형 시업체계분석모델에 의해 제시된 긴잎소나무 임분의 적정 시업체제분석 결과들을 이용하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.174-176
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• 2005

This treatise studies composing process that renew information mastered by interactive experience between environment and system via network among individuals. In the previous study map information regarding free space is learned by using of reinforced learning algorithm, which enable each individual to construct optimal action policy. Based on those action policy each individuals can obtain optimal path. Moreover decision process to distinguish best optimal path by comparing those in the network composed of each individuals is added. Also information about the finally chosen path is being updated. A self renewing method of each system information by sharing the each individual data via network is proposed Data enrichment by shilling the information of many maps not in the single map is tried Numerical simulation is conducted to confirm the propose concept. In order to prove its suitability experiment using micro-mouse by integrating and comparing the information between individuals is carried out in various types of map to reveal successful result.

• 한국정밀공학회지
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• 제19권9호
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• pp.111-117
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• 2002

In most machining companies, operators decide the cutting condition, a pair of spindle speed (5) and table federate (F) by experience and subjective judgment. As cutting conditions are determined by operators' experience and ability, inconsistent cutting conditions are given in same operating conditions. The objective of this study is to develop the cutting condition decision system which utilizes shop data and predicts tool life by neural network and eventually leads to the optimal cutting condition. The production time per piece is considered for an optimization object. We will discuss the process of an optimal cutting condition decision by neural network. By this process, a series of shop data is stored. And neural network is constructed for prediction of tool life and the optimal cutting condition is recommended from a cutting condition decision system using the stored shop data. The results show that the developed system is rational in searching the optimal cutting conditions on job operations.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅲ
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• pp.1267-1270
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• 2003

In this paper, we propose a optimal design method of the LVQ network. The proposed method determines the initial reference vectors and optimal network structure using the winning expectation of output neurons of SOM. In order to verify the effectiveness of the proposed method, we performed experiments on the Fisher's IRIS data. The experimental results showed that the proposed method improves considerably on the performance of the conventional LVQ networks.