• Journal of Korean Society of Steel Construction
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• v.17 no.6 s.79
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• pp.661-672
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• 2005

For the efficient stochastic optimization of steel structures for which a large number of analyses is required, artificial neural networks,which have emerged as a powerful tool that could have been used to replace time-consuming procedures in many scientific or engineering applications, are applied. They are utilized for the solution of the equilibrium equations resulting from the application of the finite element method in connection with the reanalysis type of problem, for which a large number of finite element analyses are required in this study. As such, the use of artificial neural networks to predict finite element analysis outputs simplifies and facilitates the performance of the stochastic optimal design of structural systems where a trained neural network is used to replace the structural reanalysis phase. Moreover, to improve efficiency of used artificial neural networks, genetic algorithm is utilized. The stochastic optimizer used in this study is an algorithm based on the evolution theory. The efficiency of the proposed procedure is examined in problems with both volume (weight) functions and real-world cost functions

• Journal of Korean Tunnelling and Underground Space Association
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• v.16 no.1
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• pp.13-24
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• 2014

This paper presents development of artificial neural network(ANN) based prediction method for section forces of TBM tunnel segment lining in an effort to develop an automatized design technique. A series of design cases were first developed and subsequently analyzed using the two-ring beam finite element model. The results were then used to form a database for use as training and validation data sets for ANN development. Using the database, optimized ANNs were developed that can readily be used to predict maximum sectional forces and their distributions. It is shown that the compute maximum section forces and their distributions by the developed ANNs are almost identical to the computed by the two-ring beam finite element model, implying that the developed ANNs can be used as design tools which expedite routine design calculation process. The results of this study indicate that the neural network model can be effectively used as a reliable and simple predictive tool for the prediction of segment sectional forces for design.

• Journal of Korean Society of Transportation
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• v.27 no.5
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• pp.195-208
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• 2009

A network design problem (NDP) formulated as a mathematical program is generally used to find an optimum value to minimize or to maximize some objectives such as total travel time, social benefit, or others. NDP has, however, some limits of describing components of travel patterns like activities and trip generation due to its modeling simplicity, and also it has difficulty in including attributes of regional planning. In order to cope with such limits, this paper extends NDP to the urban planning field and proposes a mathematical program which can describe the interactions between urban social activities and transportation planning. Based on this model the authors try to optimize both urban activities and the transportation system. The model developed in this paper is tested to assess its application with a real-size regional transportation network.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.6D
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• pp.829-837
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• 2011

Construction cost estimation in planning phase which calculates the cost for performing construction tasks is used for various ways. Meanwhile, in the case of road construction, the existing cost estimating method in early phase based on numerical mean value of the past is not accurate to be used. This paper propose neural network model for estimating road construction cost in planning phase to solve the limit of current cost estimating method. The model was designed using past road construction bidding records, and variables of model were optimized through trial and error. The estimation result of the model was compared with regression analysis and government's standard and it was verified that the model is better in accuracy. It is expected that the proposed model will be used for road cost estimation in planning phase.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.05a
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• pp.1465-1468
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• 2005

유선망에 최적화 되도록 설계된 TCP는 무선망에 적용되었을 경우 무선망의 특성에 의해 발생하는 데이터의 손실을 망의 혼잡에 의한 손실로 인식하여 불필요한 혼잡 제어 메커니즘을 수행하여 망의 성능을 떨어뜨리는 문제가 발생 된다. 본 논문에서는 이 같은 문제점을 보완하기 위해 제안된 Snoop의 성능을 TCP와 비교 분석하고 앞으로 진행될 연구를 제안한다.

• Proceedings of the Korean Institute of Industrial Safety Conference
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• 2000.11a
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• pp.287-292
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• 2000

최근에 각종 SOC사업이 본격화되면서 고속도로망 및 도시교통망 확충이 가속화되어 장대 터널이 급증하고 있을 뿐만 아니라 차량의 급속한 증가로 차량배기가스에 의한 터널내부 환경의 악화가 문제시되고 있다. 특히 도로터널은 반밀폐 공간으로 터널내에서의 사고는 인명피해와 막대한 재산 피해로 이어질 수 있으므로 안전운전을 위한 제반설비 및 대책이 필요하며 안전운행을 위한 가시거리 확보 및 쾌적한 환경에 대한 요구가 대두되고 있다. 따라서 터널에서 이와 같은 요구를 만족하기 위해서 기계환기설비가 투입되고 있으며 이에 대한 최적화 설계에 대한 필요성이 높아지고 있다.(중략)

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.1B
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• pp.15-30
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• 2000

The important considerations in the design of fiber-optic networks are reliability and survivability preparing against a failure. The SDH(Synchronous Digital Hierarchy), the international standard of optical transmission, offers several network reconfiguration methods that enable network to be automatically restored from failure. One of the methods is the SHR(Self Healing Ring), which is a ring topology system. Most network providers have constructed their backbone networks with SHR architecture since it can provide survivability economically. The network architecture has eventually evolved into a multi-ring network comprised of interconnected rings. This paper addresses multi-ring network design problems is to minimize ring-construction cost. This problem can be formulated with MIP(mixed integer programming) model. However, it is difficult to solve the model within reasonable computing time on a large scale network because the model is NP-complete. Furthermore, in practice we should consider the problem of routing demands on rings to minimize total cost. This routing problem involves multiplex bundling at the intermediate nodes. A family of heuristic algorithms is presented for this problem. These algorithms include gateway selection and routing of inter-ring demands as well as load balancing on single rings. The developed heuristic algorithms are applied to some network provider's regional and long-distance transmission networks. We show an example of ring design and compare it with another ring topology design. Finally, we analysis the effect bundling.

• The Transactions of the Korea Information Processing Society
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• v.7 no.2
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• pp.385-391
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• 2000

Recently, neural network research for forecasting the consecutive controlling rules of the future is being progressed, using the series data which are different from the traditional statistical analysis methods. In this paper, we suggest the pruning algorithm for the fast and exact weather forecast that excludes the hidden layer of the early optional designed nenral network. There are perform the weather forecast experiments using the 22080 kinds of weather data gathered from 1987 to 1996 for proving the efficiency of this suggested algorithm. Through the experiments, the early optional composed $26{\times}50{\times}1$ nenral network became the most suitable $26{\times}2{\times}1$ structure through the pruning algorithm suggested, in the optimum neural network $26{\times}2{\times}1$, in the case of the error temperature ${\pm}0.5^{\circ}C$, the average was 33.55%, in the case of ${\pm}1^{\circ}C$, the average was 61.57%, they showed more superior than the average 29.31% and 54.47% of the optional designed structure, also. we can reduce the calculation frequency more than maximum 25 times as compared with the optional sturcture neural network in the calculation frequencies.

• Proceedings of the Korea Contents Association Conference
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• 2017.05a
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• pp.445-446
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• 2017

신재생 에너지 분야의 산업과 기술의 발달과 함께 스마트 그리드와 에너지 저장 시스템이 주목받고 있다. 기존의 에너지 공급망에 정보통신기술(ICT)을 접목하여 에너지 공급자와 소비자가 양방향으로 실시간 정보를 교환함으로써 에너지 효율을 최적화하는 차세대 지능형 에너지망에 대한 수요가 늘고 관리기술에 대한 요구가 증가함에 따라, 다양한 에너지 공급원마다의 최적화된 운영시스템을 요구하고 있다. 본 논문에서는 산업분야에서 사용되고 있는 태양열에 기반한 시스템과 누적된 기상 데이터와 집열량에 대한 데이터를융합분석하여 수평면전일사량을 예측할 수 있는 시스템을 제안한다.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.295-296
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• 2008

본 논문에서는 이동통신 시스템이 진화됨에 따라 다양한 서비스의 출현과 사용자 수가 증가됨에 따라 무선망 설계 및 최적화 시에 필요성이 부각되고 있는 용량 분석 및 예측을 수행하기 위해 필요한 요소들을 기술하고 이러한 요소들을 고려하여 구현된 용량 분석 시뮬레이터에 대하여 기술 한다