• 한국정밀공학회지
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• 제15권4호
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• pp.15-26
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• 1998

Full car model is needed for investigating as a entire dynamics of vehicle. In this study, 7DOF of full car model's dynamics is selected. This paper proposes the output feedback controller based on optimal control theory. Input data and output data from the optimal controller are used for neural network system identification of the suspension system. To do system identification, neural network which has robustness against nonlinearities and disturbances is adapted. This study uses back-propagation algorithm to train a multil-layer neural network. After obtaining a neural network model of a suspension system, a neuro-controller is designed. Neuro-controller controls suspension system with off-line learning method and multistep ahead prediction model based on the neural network model and a neuro-controller. The optimal controller and the neuro-controller are designed and then, both performances are compared through. For simulation, sinusoidal and rectangular virtual bumps are selected.

• 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.

• 제어로봇시스템학회논문지
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• 제20권7호
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• pp.750-755
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• 2014

Product shortage which causes backordering and/or lost sales cost is very popular in chemical industries, especially in commodity polymer business. This study deals with backordering cost in the supply chain optimization model under the framework of process-inventory network. Classical economic order quantity model with backordering cost suggested optimal time delay and lot size of the final product delivery. Backordering can be compensated by advancing production/transportation of it or purchasing substitute product from third party as well as product delivery delay in supply chain network. Optimal solutions considering all means to recover shortage are more complicated than the classical one. We found three different solutions depending on parametric range and variable bounds. Optimal capacity of production/transportation processes associated with the product in backordering can be different from that when the product is not in backordering. The product shipping cycle time computed in this study was smaller than that optimized by the classical EOQ model.

• 한국수자원학회논문집
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• 제44권12호
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• pp.1001-1013
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• 2011

이웃한 상수도시스템의 공급 가능지역이 중첩될 경우, 이들 시스템을 연계함으로써 경제성과 수질 조건을 만족시키는 조건별 용수공급체계를 구축하는 것이 필요하다. 용수수요 조건별 경제적 급수구역과 최적 펌프운영율을 산정하기 위하여 관망수리해석 모형(EPAnet)과 네트워크 최적화모형(KModSim)을 연계 하는 최적 네트워크모형을 개발하였다. 개발된 최적 네트워크 모형을 사등가압장, 구천댐 그리고 연초댐의 3개 상수원이 존재하는 거제지역 상수도시스템에 적용하고 2007년 운영 결과와 비교하는 방법으로 모형을 검정하였다. 최적 네트워크 모형의 적용성을 검토하기 위하여, 2011년 용수자료를 이용하여경제적급수구역변경에따른펌프운영및 수질의 적정성을평가 하였다. 평가결과본 모형은 수량, 경제성 그리고 수질을 모두 만족하는 최적해를 구하는 것으로 나타나 송배수계통간의 최적 설계 혹은 최적연계운영율을 구하기 위한 모형으로 활용이 가능하다.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
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• pp.133-141
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• 2001

Since the computing environment changes very rapidly, the estimation of software effort is very difficult because it is not easy to collect a sufficient number of relevant cases from the historical data. If we pinpoint the cases, the number of cases becomes too small. However is we adopt too many cases, the relevance declines. So in this paper we attempt to balance the number of cases and relevance. Since many researches on software effort estimation showed that the neural network models perform at least as well as the other approaches, so we selected the neural network model as the basic estimator. We propose a search method that finds the right level of relevant cases for the neural network model. For the selected case set. eliminating the qualitative input factors with the same values can reduce the scale of the neural network model. Since there exists a multitude of combinations of case sets, we need to search for the optimal reduced neural network model and corresponding case, set. To find the quasi-optimal model from the hierarchy of reduced neural network models, we adopted the beam search technique and devised the Case-Set Selection Algorithm. This algorithm can be adopted in the case-adaptive software effort estimation systems.

• 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.

• 대한산업공학회지
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• 제24권2호
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• pp.241-249
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• 1998

In this paper, we seek to find an optimal allocation of link capacity in a data communication network. The architecture of the data communication network considered in the study is an online-service network based on public switched telephone network(PSTN) and packet switched data network(PSDN). In designing the architecture of the network, we need to deal with various measures of quality of service(QoS). Two important service measures are the call blocking probability in PSTN and the data transfer delay time in PSDN. Considering the tradeoff between the call blocking probability and the data transfer delay time in the network, we have developed the optimal link capacity allocation model that minimizes the total link cost, while guarantees the call blocking probability and the data transfer delay time within an acceptable level of QoS. This problem can be formulated as a non-linear integer programming model. We have solved the problem with tabu search and simulated annealing methods. In addition, we have analyzed the sensitivity of the model and provided the insight of the model along with computational results.

• Journal of Power Electronics
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• 제19권5호
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• pp.1289-1302
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• 2019

In this paper, an optimal allocation method of a hybrid active power filter in an active distribution network is designed based on the differential evolution algorithm to resolve the harmonic generation problem when a distributed generation system is connected to the grid. A distributed generation system model in the calculation of power flow is established. An improved back/forward sweep algorithm and a decoupling algorithm are proposed for fundamental power flow and harmonic power flow. On this basis, a multi-objective optimization allocation model of the location and capacity of a hybrid filter in an active distribution network is built, and an optimal allocation scheme of the hybrid active power filter based on the differential evolution algorithm is proposed. To verify the effect of the harmonic suppression of the designed scheme, simulation analysis in an IEEE-33 nodes model and an experimental analysis on a test platform of a microgrid are adopted.

• Management Science and Financial Engineering
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• 제6권2호
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• pp.29-45
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• 2000

We consider the design of a two-level telecommunication network having logical full-mesh/star topology, with the implementation of conduit systems taken together. The design problem is then viewed as consisting of three subproblems: locating hub facilities, placing a conduit network, and installing cables therein to configure the logical full-mesh/star network. Without partitioning into subproblems as done in the conventional approach, the whole problem is directly dealt with in a single integrated framework, inspired by some recent successes with the approach. We successfully formulate the problem as a variant of the classical multicommodity flow model for the fixed charge network design problem, aided by network augmentation, judicious commodity definition, and some flow restrictions. With our optimal model, we solve some randomly generated sample problems by using CPLEX MIP program. From the computational experiments, it seems that our model can be applied to the practical problem effectively.

• 제어로봇시스템학회논문지
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• 제16권5호
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• pp.476-480
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• 2010

This study deals with stockout costs in the supply chain optimization model under the framework of batch-storage network. Stockout is very popular in chemical industries. Estimating stockout cost involves an understanding of customer reactions to a seller being out of stock at the time the customer wants to buy an item. This involves massively non-trivial work such as direct customer interviews and extensive mail survey. In this study, we will introduce a new interpretation of stockout costs combined with batchstorage network optimization model and thus suggest an easy way of estimating stockout costs. Optimization model suggest that optimal process and storage sizes considering stockout cost are smaller than those that do not consider stockout cost. An illustrative example support the analytical results.