• 한국멀티미디어학회논문지
• /
• 제10권12호
• /
• pp.1645-1654
• /
• 2007

In this paper, we study the problem of load balancing routing in clustered-based wireless mesh network in order to enhance the overall network throughput. We first address the problems of cluster allocation in wireless mesh network to achieve load-balancing state. Due to the complexity of the problem, we proposed a simplified algorithm using gradient load-balancing model. This method searches for a localized optimal solution of cluster allocation instead of solving the optimal solution for overall network. To support for load-balancing algorithm and reduce complexity of topology control, we also introduce limited broadcasting between two clusters. This mechanism maintain shortest path between two nodes in adjacent clusters while minimizing the topology broadcasting complexity. The simulation experiments demonstrate that our proposed model achieve performance improvement in terms of network throughput in comparison with other clustering methods.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2005년도 ICCAS
• /
• pp.1716-1722
• /
• 2005

Fuzzy logic, neural network, fuzzy-neural network play an important as the key technology of linguistic modeling for intelligent control and decision in complex systems. The fuzzy-neural network (FNN) learning represents one of the most effective algorithms to build such linguistic models. This paper proposes bacteria foraging algorithm based optimal learning fuzzy-neural network (BA-FNN). The proposed learning scheme is the fuzzy-neural network structure which can handle linguistic knowledge as tuning membership function of fuzzy logic by bacteria foraging algorithm. The learning algorithm of the BA-FNN is composed of two phases. The first phase is to find the initial membership functions of the fuzzy neural network model. In the second phase, bacteria foraging algorithm is used for tuning of membership functions of the proposed model.

• KIEAE Journal
• /
• 제16권3호
• /
• pp.89-94
• /
• 2016

Purpose: This study aimed at developing an artificial neural network (ANN) model to predict the optimal start moment of the setback temperature during the normal occupied period of a building. Method: For achieving this objective, three major steps were conducted: the development of an initial ANN model, optimization of the initial model, and performance tests of the optimized model. The development and performance testing of the ANN model were conducted through numerical simulation methods using transient systems simulation (TRNSYS) and matrix laboratory (MATLAB) software. Result: The results analysis in the development and test processes revealed that the indoor temperature, outdoor temperature, and temperature difference from the setback temperature presented strong relationship with the optimal start moment of the setback temperature; thus, these variables were used as input neurons in the ANN model. The optimal values for the number of hidden layers, number of hidden neurons, learning rate, and moment were found to be 4, 9, 0.6, and 0.9, respectively, and these values were applied to the optimized ANN model. The optimized model proved its prediction accuracy with the very storing statistical correlation between the predicted values from the ANN model and the simulated values in the TRNSYS model. Thus, the optimized model showed its potential to be applied in the control algorithm.

• 한국농공학회논문집
• /
• 제46권1호
• /
• pp.121-131
• /
• 2004

Transportation and logistics of agricultural products have been one of the major interests of many researches. Most of researches have been limited to presuming these as a first dimensional process or considering only economic value of agricultural products at each stage of logistics. However, the particular characteristics of agricultural products, such as quality change during transportation or extensively scattered origins, require examining these problems as a whole system. Network model has been adopted to represent nodes, which stand for spatial location of demand and supply of agricultural products, and communication between these nodes. Based on network theory and advanced marketing potential function, an optimal routes selection model is developed. The model employed network simplex method for routes optimization. The application of the model focused on transportation network organization to reflect different market prices for different locations and resulted in optimum routes and profit improvement of the applied agricultural product.

• 대한교통학회지
• /
• 제20권5호
• /
• pp.193-206
• /
• 2002

신호교차로로 구성된 네트워크의 시스템최적 신호시간산정을 위해 Cell Transmission 이론을 교통류 모형으로 활용한 신호최적화 모형을 제안한다. Cell Transmission 모형은 기존에 소개된 신호최적화 모형과는 달리 충격파, 대기행렬의 길이, 그리고 하류부 교차로 대기행렬의 역류(Spillback)과 같은 과포화 현상을 표현하는데 적절한 이론적이고 실제적인 배경을 지원한다. 모형에서 기점을 출발한 수요차량은 종점에 도착할 때까지 경로선택을 통해서, 그리고 신호시스템은 이러한 수요의 움직임 고려하여 신호시간요소의 최적화를 통한 네트워크의 비용을 최소화하기 위해 서로 협력한다는 의미에서 제안된 모형은 시스템 최적화를 의미한다. 모형은 혼합정수계획법으로 정식화되며 최적신호전략과 고정신호전략간의 실험계획을 통해 구축된 모형을 비교·평가한다.

• 한국전자거래학회지
• /
• 제1권2호
• /
• pp.161-173
• /
• 1996

It Is a typical scenario in concurrent engineering/design that different perspectives of each team members participating In the project exist, and those perspectives lead to conflicting decisions. The model 'resolution network' proposed in this work provides system-mediated resolution for all related team engineers to consider to optimize the manufacture in general. This paper focuses on development of the general architecture of the model and a search engine called Mediator to determine a resolution network from a given constraint network. The Mediator manages the constraint network, determines the most optimistic resolution called optimal point in terms of satisfying overall production goal , and use the optimal point to mediate controversial issues among teams. The biggest merit of our model is that it provides teams with resolution with logical and rational reasoning.

• 경영과학
• /
• 제24권2호
• /
• pp.127-142
• /
• 2007

This study deals with the optimal design of mobile access network connecting base stations(BSs) and mobile switching centers(MSCs). Generally mobile operators constitute their access networks by leasing communication lines. Using the characteristic of leased line rate based on administration region, we build an optimization model for mobile access network design which has much smaller number of variables than the existing researches. And we develop a GUI based optimization tool integrating the well-known softwares such as MS EXCEL. MS VisualBasic, MS PowerPoint and Ip_solve, a freeware optimization software. Employing the current access network configuration of a Korean mobile carrier, this study using the optimization tool obtain an optimal solution for both single MSC access network and nation-wide access network. Each optimal access network achieves 7.45% and 9.49% save of lease rate, respectively. Considering the monthly charge and total amount of lease line rate, our optimization tool provides big amount of save in network operation cost. Besides the graphical representation of access networks makes the operator easily understand and compare current and optimal access networks.

• 제어로봇시스템학회논문지
• /
• 제4권6호
• /
• pp.802-810
• /
• 1998

The purpose of this study is to find the analytic solution of determining the optimal capacity of processes and storages to meet the product demand. Recent trend to reduce product delivery time and to provide high quality product to customer requires the increasing capacity of storage facilities. However, the cost of constructing and operating storage facilities is becoming substantial because of increasing land value, environmental and safety concern. Therefore, reasonable decision making about the capacity of processes and storages is important subject for industries. The industrial solution for this subject is to use the classical economic lot sizing method, EOQ(Economic Order Quantity) model, trimmed with practical experience but the unrealistic assumption of EOQ model is not suitable for the chemical plant design with highly interlinked processes and storages. This study, a first systematic attempt for this subject, clearly overcomes the limitation of classical lot sizing method. The superstructure of the plant consists of the network of serially and/or parallelly interlinked processes and storages. A novel production and inventory analysis method, PSW(Periodic Square Wave) model, is applied. The objective function of optimization is minimizing the total cost composed of setup and inventory holding cost. The advantage of PSW model comes from the fact that the model provide a set of simple analytic solution in spite of realistic description of material flow between process and storage. The resulting simple analytic solution can greatly enhance the proper and quick investment decision for the preliminary plant design confronting diverse economic situation.

• 한국수자원학회:학술대회논문집
• /
• 한국수자원학회 1989년도 수공학논총 제31권
• /
• pp.63-70
• /
• 1989

• 정보처리학회논문지:소프트웨어 및 데이터공학
• /
• 제6권12호
• /
• pp.565-572
• /
• 2017

본 연구는 기존의 수요 예측 등의 시계열 연구에서 주로 사용되는 ARIMA 모형의 어려움을 극복하고자 인공신경망(Artificial neural network) 모형을 이용하여 한국 프로 야구 관중 수를 예측하였다. 훈련 자료로는 2015년 3월부터 9월까지의 일별 KBO 관중 수 자료를 대상으로 하였다. 전방향 신경망(Feedforward neural network)의 모형 훈련 과정에서, 그리드 탐색(Grid search)을 적용하여 최적의 초모수(Hyperparameter)를 찾고자 하였다. 그 결과, 그리드 탐색법의 최적 모형을 이용한 평균 절대 백분율 오차(MAPE)는 평균 20.9% 였다. 앙상블 기법을 이용한 모형의 MAPE는 평균 20.0%였다. 이는 다중회귀와 비교해보았을 때, 평균적으로 각각 26.3%, 30.3% 높은 예측력을 보인다.