• Title/Summary/Keyword: Optimal Network Design

Search Result 742, Processing Time 0.033 seconds

Neural Network Active Control of Structures with Earthquake Excitation

  • Cho Hyun Cheol;Fadali M. Sami;Saiidi M. Saiid;Lee Kwon Soon
    • International Journal of Control, Automation, and Systems
    • /
    • v.3 no.2
    • /
    • pp.202-210
    • /
    • 2005
  • This paper presents a new neural network control for nonlinear bridge systems with earthquake excitation. We design multi-layer neural network controllers with a single hidden layer. The selection of an optimal number of neurons in the hidden layer is an important design step for control performance. To select an optimal number of hidden neurons, we progressively add one hidden neuron and observe the change in a performance measure given by the weighted sum of the system error and the control force. The number of hidden neurons which minimizes the performance measure is selected for implementation. A neural network was trained for mitigating vibrations of bridge systems caused by El Centro earthquake. We applied the proposed control approach to a single-degree-of-freedom (SDOF) and a two-degree-of-freedom (TDOF) bridge system. We assessed the robustness of the control system using randomly generated earthquake excitations which were not used in training the neural network. Our results show that the neural network controller drastically mitigates the effect of the disturbance.

Optimal Design of Water Supply System using Multi-objective Harmony Search Algorithm (Multi-objective Harmony Search 알고리즘을 이용한 상수도 관망 다목적 최적설계)

  • Choi, Young-Hwan;Lee, Ho-Min;Yoo, Do-Guen;Kim, Joong-Hoon
    • Journal of Korean Society of Water and Wastewater
    • /
    • v.29 no.3
    • /
    • pp.293-303
    • /
    • 2015
  • Optimal design of the water supply pipe network aims to minimize construction cost while satisfying the required hydraulic constraints such as the minimum and maximum pressures, and velocity. Since considering one single design factor (i.e., cost) is very vulnerable for including future conditions and cannot satisfy operator's needs, various design factors should be considered. Hence, this study presents three kinds of design factors (i.e., minimizing construction cost, maximizing reliability, and surplus head) to perform multi-objective optimization design. Harmony Search (HS) Algorithm is used as an optimization technique. As well-known benchmark networks, Hanoi network and Gyeonggi-do P city real world network are used to verify the applicability of the proposed model. In addition, the proposed multi-objective model is also applied to a real water distribution networks and the optimization results were statistically analyzed. The results of the optimal design for the benchmark and real networks indicated much better performance compared to those of existing designs and the other approach (i.e., Genetic Algorithm) in terms of cost and reliability, cost, and surplus head. As a result, this study is expected to contribute for the efficient design of water distribution networks.

Optimal design of DNP 3.0 network for the Distribution Automation System (배전자동화통신망을 위한 DNP 3.0 최적 설계 방안)

  • Kim, Tae-Gyeong
    • Proceedings of the KIEE Conference
    • /
    • 2009.07a
    • /
    • pp.422_423
    • /
    • 2009
  • DNP 3.0 is the most widely used data communication protocol for electric power control systems. KEPCO(Korea Electric Power Corporation) also uses DNP 3.0 as a data transmission protocol for the DAS(Distribution Automation System) and the SCADA system of the transmmission system. But DNP 3.0 is one of the oldest industrial standard having many restrictions and there are many considerations for optimal design of DNP 3.0 network for the Distribution Automation System.

  • PDF

Wireless sensor network design for large-scale infrastructures health monitoring with optimal information-lifespan tradeoff

  • Xiao-Han, Hao;Sin-Chi, Kuok;Ka-Veng, Yuen
    • Smart Structures and Systems
    • /
    • v.30 no.6
    • /
    • pp.583-599
    • /
    • 2022
  • In this paper, a multi-objective wireless sensor network configuration optimization method is proposed. The proposed method aims to determine the optimal information and lifespan wireless sensor network for structural health monitoring of large-scale infrastructures. In particular, cluster-based wireless sensor networks with multi-type of sensors are considered. To optimize the lifetime of the wireless sensor network, a cluster-based network optimization algorithm that optimizes the arrangement of cluster heads and base station is developed. On the other hand, based on the Bayesian inference, the uncertainty of the estimated parameters can be quantified. The coefficient of variance of the estimated parameters can be obtained, which is utilized as a holistic measure to evaluate the estimation accuracy of sensor configurations with multi-type of sensors. The proposed method provides the optimal wireless sensor network configuration that satisfies the required estimation accuracy with the longest lifetime. The proposed method is illustrated by designing the optimal wireless sensor network configuration of a cable-stayed bridge and a space truss.

Optimal Network Design with Hooke-and-Jeeves Algorithm (Hooke-and-Jeeves 기법에 의한 최적가로망설계)

  • 장현봉;박창호
    • Journal of Korean Society of Transportation
    • /
    • v.6 no.1
    • /
    • pp.5-16
    • /
    • 1988
  • Development is given to an optimal network design method using continuous design variables. Modified Hooke-and-Jeeves algorithm is implemented in order to solve nonlinear programming problem which is approximately equivalent to the real network design problem with system efficiency crieteria and improvement cost as objective function. the method was tested for various forms of initial solution, and dimensions of initial step size of link improvements. At each searching point of evaluating the objective function, a link flow problem was solved with user equilibrium principles using the Frank-Wolfe algorithm. The results obtained are quite promising interms fo numbers of evaluation, and the speed of convergence. Suggestions are given to selections of efficient initial solution, initial step size and convergence criteria. An approximate method is also suggested for reducing computation time.

  • PDF

Preform Design of the Bevel Gear for the Warm Forging using Artificial Neural Network (신경망을 이용한 정밀 베벨기어의 온간단조 예비성형체 설계)

  • 김동환;김병민
    • Journal of the Korean Society for Precision Engineering
    • /
    • v.20 no.7
    • /
    • pp.36-43
    • /
    • 2003
  • In this paper, the warm forging process sequence has been determined to manufacture the warm forged product for the precision bevel gear used as the differential gear unit of a commercial automobile. The preform shape of bevel gear influences the dimensional accuracy and stiffness of final product. So, the design parameters related preform shape such as aspect ratio and chamfer length having an influence the formability of forged product are analyzed. Then the optimal conditions of design parameters have been selected by artificial neural network (ANN). Finally, to verify the optimal preform shape, the experiments of the warm forging of the bevel gear have been executed. The proposed method can give more systematic and economically feasible means for designing preform shape in metal forming process.

Optimal Model Design of Software Process Using Genetically Fuzzy Polynomial Neyral Network (진화론적 퍼지 다항식 뉴럴 네트워크를 이용한 소프트웨어 공정의 최적 모델 설계)

  • Lee, In-Tae;Oh, Sung-Kwun;Kim, Hyun-Ki
    • Proceedings of the KIEE Conference
    • /
    • 2005.07d
    • /
    • pp.2873-2875
    • /
    • 2005
  • The optimal structure of the conventional Fuzzy Polynomial Neural Networks (FPNN)[3] depends on experience of designer. For the conventional Fuzzy Polynomial Neural Networks, input variable number, number of input variable, number of Membership Functions(MFs) and consequence structures are selected through the experience of a model designer iteratively. In this paper, we propose the new design methodology to find the optimal structure of Fuzzy Polymomial Neural Network by using Genetic Algorithms(GAs)[4, 5]. In the sequel, It is shown that the proposed Advanced Genetic Algorithms based Fuzzy Polynomial Neural Network(Advanced GAs-based FPNN) is more useful and effective than the existing models for nonlinear process. We used Medical Imaging System(MIS)[6] data to evaluate the performance of the proposed model.

  • PDF

Evaluation of Geotechnical Parameters Based on the Design of Optimal Neural Network Structure (최적의 인공신경망 구조 설계를 통한 지반 물성치 추정)

  • Park Hyun-Il;Hwang Dae-Jin;Kweon Gi-Chul;Lee Seung-Rae
    • Journal of the Korean Geotechnical Society
    • /
    • v.21 no.9
    • /
    • pp.25-34
    • /
    • 2005
  • This paper proposes a selection methodology composed of neural network (NN) and genetic algorithm (GA) to design optimal NN structure. We combine the characteristics of GA and NN to reduce the computational complexity of artificial intelligence applications and increase the precision of NN' prediction in the design of NN structure. Genetic selection approach of design parameters of NN is introduced to obtain optimal NN structure. Analyzed results for geotechnical problems are given to evaluate the performance of the proposed hybrid methodology.

Optimal Network Design Using Sensitivity Analysis for Variable Demand Network Equilibrium (가변수요 통행배정의 민감도 분석을 통한 최적가로망 설계)

  • 권용석;박병정;이성모
    • Journal of Korean Society of Transportation
    • /
    • v.19 no.1
    • /
    • pp.89-99
    • /
    • 2001
  • The conventional studies on equilibrium network design problem(ENDP) with fixed travel demand models assume that the future OD travel demand might not be changed even if the structure and the capacity of the network are improved. But this fixed demand assumption may loose its validity in the long-range network design because OD travel demand actually shifts with the network service level. Thus, it is desirable to involve the variable travel demand which is determined endogenously in the model in the optimal network design. In this paper a hi-level model formulation and solution procedure for ENDP with variable travel demand are presented. Firstly It is considered how to measure the net user benefits to be derived from the improved in link capacities, and the equilibrium network design problem considered here is to maximize the increase of net user benefit which results from a set of lift capacity enhancements within the budget constraints, while the OD travel demands and link travel times are obtained by solving the lower level network equilibrium problem with variable demand. And secondly sensitivity analysis is carried out to find the links to which the network equilibrium flow pattern is the most sensitive. Finally numerical example with simple network is carried out to test the validity of the model.

  • PDF