• Title/Summary/Keyword: weighting optimization

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Design Optimization of Centrifugal Pumps (원심 펌프의 최적 설계)

  • Oh, Hyoung Woo;Chung, Myung Kyoon;Kim, Sang Chul;Yang, Keun Yung;Ha, Jin Soo
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.23 no.2
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    • pp.254-261
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    • 1999
  • An optimal design code for centrifugal pumps has been developed to determine geometric and fluid dynamic variables under appropriate design constraints. The optimization problem has been formulated with a nonlinear objective function to minimize one, two or all of the fluid dynamic losses, the net positive suction head required and the product price of a pump stage depending on the weighting factors selected as the design compromise. The optimal solution Is obtained by means of the Hooke and Jeeves direct search method. The performance analysis Is based on the mean streamline analysis using the present state-of-the-art loss correlations. The optimized efficiency and design variables of centrifugal pumps are presented in this paper as a function of non-dimensional specific speed in the range, $0.5{\leq}N$, ${\leq}1.3$. The diagrams presented herein can be used efficiently in the preliminary design phase of centrifugal pumps.

Application of multi-objective genetic algorithm for waste load allocation in a river basin (오염부하량 할당에 있어서 다목적 유전알고리즘의 적용 방법에 관한 연구)

  • Cho, Jae-Heon
    • Journal of Environmental Impact Assessment
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    • v.22 no.6
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    • pp.713-724
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    • 2013
  • In terms of waste load allocation, inequality of waste load discharge must be considered as well as economic aspects such as minimization of waste load abatement. The inequality of waste load discharge between areas was calculated with Gini coefficient and was included as one of the objective functions of the multi-objective waste load allocation. In the past, multi-objective functions were usually weighted and then transformed into a single objective optimization problem. Recently, however, due to the difficulties of applying weighting factors, multi-objective genetic algorithms (GA) that require only one execution for optimization is being developed. This study analyzes multi-objective waste load allocation using NSGA-II-aJG that applies Pareto-dominance theory and it's adaptation of jumping gene. A sensitivity analysis was conducted for the parameters that have significant influence on the solution of multi-objective GA such as population size, crossover probability, mutation probability, length of chromosome, jumping gene probability. Among the five aforementioned parameters, mutation probability turned out to be the most sensitive parameter towards the objective function of minimization of waste load abatement. Spacing and maximum spread are indexes that show the distribution and range of optimum solution, and these two values were the optimum or near optimal values for the selected parameter values to minimize waste load abatement.

A Finite Element Analysis and Shape Optimal Design with Specified Stiffness for U-typed Bellows (U형 벨로우즈의 유한요소해석과 특정 강성을 위한 형상최적설계)

  • Koh, K.G.;Suh, Y.J.;Park, G.J.
    • Transactions of the Korean Society of Automotive Engineers
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    • v.3 no.6
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    • pp.96-111
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    • 1995
  • A bellows is a component installed in the automobile exhaust system to reduce the impact from an engine. It's stiffness has a great influence on the natural frequency of the system. Therefore, it must be designed to keep the specified stiffness that requires in the system. This study present the finite element analysis of U-typed bellows using a curved conical frustum element and the shape optimal design with specified stiffness. The finite element analysis is verified by comparing with the experimental results. In the shape optimal design, the weight is considered as the cost function. The specified stiffness from the system design is transformed to equality constraints. The formulation has inequality constraints imposed on the fatigue limit, the natural frequencies, the buckling load and the manufacturing conditions. A procedure for shape optimization adopts a thickness, a corrugation radius, and a length of annular plate as optimal design variables. The external loading conditions include the axial and lateral loads with a boundary condition fixed at an end of the bellows. The recursive quadratic programming algorithm is selected to solve the problem. The result are compared with the existing bellows, and the characteristics of the bellows is investigated through the optimal design process. The optimized shape of the bellows are expected to give quite a good guideline to the practical design.

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Optimal Design of Automotive Seat Back Frame Using Finite Element Analysis (유한요소해석을 이용한 차량용 시트 백 프레임의 최적설계)

  • Shin, Hyeonho;Kang, Hee Yong;Yang, Sung Mo
    • Journal of Auto-vehicle Safety Association
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    • v.11 no.4
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    • pp.57-62
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    • 2019
  • The seat back frame of the vehicle is subjected to load on the passenger behavior. Because of steel material, it is necessary to optimize the frame considering lightweight and safety. In this paper, finite element analysis is used for the optimal design of the seat back frame. First, a lightweight material is applied to reduce the weight of the seat back frame. Secondly, the design position of the pipe part fastened in the seat back frame was selected by considering the strength against the load generated by the occupant. Third, the shape of the side frame was derived by performing the phase optimization analysis for the AFT load condition. And we have compared the initial model with the optimal model to verify the light weighting and safety. As a result, the optimal design model of the seat back frame satisfying the weight reduction and safety has been proposed.

IMPROVEMENT OF RIDE AND HANDLING CHARACTERISTICS USING MULTI-OBJECTIVE OPTIMIZATION TECHNIQUES

  • KIM W. Y.;KIM D. K.
    • International Journal of Automotive Technology
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    • v.6 no.2
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    • pp.141-148
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    • 2005
  • In order to reduce the time and costs of improving the performance of vehicle suspensions, the techniques for optimizing damping and air spring characteristic were proposed. A full vehicle model for a bus is constructed with a car body, front and rear suspension linkages, air springs, dampers, tires, and a steering system. An air spring and a damper are modeled with nonlinear characteristics using experimental data and a curve fitting technique. The objective function for ride quality is WRMS (Weighted RMS) of the power spectral density of the vertical acceleration at the driver's seat, middle seat and rear seat. The objective function for handling performance is the RMS (Root Mean Squares) of the roll angle, roll rate, yaw rate, and lateral acceleration at the center of gravity of a body during a lane change. The design variables are determined by damping coefficients, damping exponents and curve fitting parameters of air spring characteristic curves. The Taguchi method is used in order to investigate sensitivity of design variables. Since ride and handling performances are mutually conflicting characteristics, the validity of the developed optimum design procedure is demonstrated by comparing the trends of ride and handling performance indices with respect to the ratio of weighting factors. The global criterion method is proposed to obtain the solution of multi-objective optimization problem.

Using GAs to Support Feature Weighting and Instance Selection in CBR for CRM

  • Ahn, Hyun-Chul;Kim, Kyoung-Jae;Han, In-Goo
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2005.11a
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    • pp.516-525
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    • 2005
  • Case-based reasoning (CBR) has been widely used in various areas due to its convenience and strength in complex problem solving. Generally, in order to obtain successful results from CBR, effective retrieval of useful prior cases for the given problem is essential. However, designing a good matching and retrieval mechanism for CBR systems is still a controversial research issue. Most prior studies have tried to optimize the weights of the features or selection process of appropriate instances. But, these approaches have been performed independently until now. Simultaneous optimization of these components may lead to better performance than in naive models. In particular, there have been few attempts to simultaneously optimize the weight of the features and selection of the instances for CBR. Here we suggest a simultaneous optimization model of these components using a genetic algorithm (GA). We apply it to a customer classification model which utilizes demographic characteristics of customers as inputs to predict their buying behavior for a specific product. Experimental results show that simultaneously optimized CBR may improve the classification accuracy and outperform various optimized models of CBR as well as other classification models including logistic regression, multiple discriminant analysis, artificial neural networks and support vector machines.

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A Study on the Minimum Production Cost of Welded Built-up Beams (용접 조립보의 최소 생산 비용에 관한 연구)

  • Chang-Doo Jang;Seung-Il Seo
    • Journal of the Society of Naval Architects of Korea
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    • v.31 no.3
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    • pp.154-164
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    • 1994
  • In this study, to find an economical production method which yields welded built-up beams with high quality, simulation techniques and optimization method are used. At first, fabrication variables such as welding current, voltage and speed and heated depth and breadth are selected and fabrication cost of a built-up beam is expressed by these parameters, which is optimized under the constraints. As advanced studies, total production cost including the fabrication cost and the material cost of the beam is expressed by the fabrication and design variables, and optimized with the design constraints by the class rules. In addition, assuming that heating for straightening is impossible. the optimization method of multi-objective functions based on the weighting method is applied to obtain the compromised optimal solutions of the total production cost and the welding deformation.

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A Robust Speaker Identification Using Optimized Confidence and Modified HMM Decoder (최적화된 관측 신뢰도와 변형된 HMM 디코더를 이용한 잡음에 강인한 화자식별 시스템)

  • Tariquzzaman, Md.;Kim, Jin-Young;Na, Seung-Yu
    • MALSORI
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    • no.64
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    • pp.121-135
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    • 2007
  • Speech signal is distorted by channel characteristics or additive noise and then the performances of speaker or speech recognition are severely degraded. To cope with the noise problem, we propose a modified HMM decoder algorithm using SNR-based observation confidence, which was successfully applied for GMM in speaker identification task. The modification is done by weighting observation probabilities with reliability values obtained from SNR. Also, we apply PSO (particle swarm optimization) method to the confidence function for maximizing the speaker identification performance. To evaluate our proposed method, we used the ETRI database for speaker recognition. The experimental results showed that the performance was definitely enhanced with the modified HMM decoder algorithm.

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A Probabilistic Method Based Protectability Evaluation of Distance Relay in Transmission Networks

  • Zhang, Wen-Hao;Choi, Myeon-Song;Lee, Seung-Jae;Lim, Il-Hyung;Rim, Seong-Jeong
    • Journal of Electrical Engineering and Technology
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    • v.3 no.3
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    • pp.346-353
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    • 2008
  • This paper defines the concept of “protectability” for the performance evaluation of distance relay considering its sensitivity and selectivity. The paper starts from the probabilistic modeling of the errors, and based on this model, a detailed explanation of protectability calculation for each zone of the distance relay is presented. An effect of the Weighting Rate and the Measurement Deviation on the protectability evaluation is also given. By considering this effect, the optimization of relay setting can be realized. The proposed method is applied to a typical model system to show its effectiveness

Optimal actuator selection for output variance constrained control

  • 김재훈
    • 제어로봇시스템학회:학술대회논문집
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    • 1993.10a
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    • pp.565-569
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    • 1993
  • In this paper, a specified number of actuators are selected from a given set of admissible actuators. The selected set of actuators is likely to use minimum control energy while required output variance constraints are guaranteed to be satisfied. The actuator selection procedure is an iterative algorithm composed of two parts; an output variance constrained control and an input variance constrained control algorithm. The idea behind this algorithm is that the solution to the first control problem provides the necessary weighting matrix in the objective function of the second optimization problem, and the sensitivity information from the second problem is utilized to delete one actuator. For variance constrained control problems, by considering a dual version of each control problem an efficient algorithm is provided, whose convergence properties turn out to be better than an existing algorithm. Numerical examples with a simple beam are given for both the input/output variance constrained control problem and the actuator selection problem.

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