• Journal of Korean Society of Rural Planning
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• v.13 no.2
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• pp.17-26
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• 2007

This study aims to develop a rational evaluation system which consists of the selection of evaluation items and the estimation of its weight for the Enhancement Program of the Quality of Life for Farmers and Fishermen and Rural Development. This system has two hierarchical steps. The first step shows the evaluation goals which are relevance, efficiency and effectiveness of the program. The second step stands for the evaluation items which have 11 sub-items such as necessity and externalization for the program, rationality of procedures, feedback and monitoring system, budgetary allocations, information activities, impacts on the program, achievements of the goals and so on. A tentative evaluation system was proposed by brainstorming and Delphi method of expert-group. Weighting values of evaluation items were calculated through pair-comparison works of expert group using stepwise matrix sheets by AHP(Analytic Hierarchy Process).

• Korean Journal of Cognitive Science
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• v.19 no.4
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• pp.477-497
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• 2008

Mood classification of blog text is an interesting problem, with a potential for a variety of services involving the Web. This paper introduces an approach to mood classification enhancements through the normalized negation n-grams which contain mood clues and corpus-specific term weighting(CSTW). We've done experiments on blog texts with two different classification methods: Enhanced Mood Flow Analysis(EMFA) and Support Vector Machine based Mood Classification(SVMMC). It proves that the normalized negation n-gram method is quite effective in dealing with negations and gave gradual improvements in mood classification with EMF A. From the selection of CSTW, we noticed that the appropriate weighting scheme is important for supporting adequate levels of mood classification performance because it outperforms the result of TF*IDF and TF.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.2
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• pp.102-110
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• 1999

The aim of this paper is to suggest a design method of the optimal model following control system using gerelic algoritlun (GA). This control system is designed by applying GA with reference model to the optimal determinination of weighting matrices Q, R that are given by LQ regulator prooblem. The method to do this is that all the diagooal elements of weighting matrices are optimized simultaneously by GA, in the search domain selected adequately. And, we design the mxiel following control system to boiler-turbine equipment by the proposed mothod. The model following control system designed by this mothod has the better command tracking perfannaoce than that of the control system designed by the trial-and-error method. The effectiveness of this cootrol System is verified by computer simulation.

• Proceedings of the KIEE Conference
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• 2002.07a
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• pp.226-228
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• 2002

This paper presents a new control approach for designing a coordinated controller for static VAR compensator system. A SVC constructed by a Fixed Capacitor and a Thyristor Controlled Reactor is designed and implemented to improve the damping of a synchronous generator, as well as controlling the system voltage. A design of linear quadratic controller based on optimal controller depends on choosing weighting matrices. A coordinated optimal controller is achieved by minimizing a quadratic performance index using dynamic programming techniques. The selection of weighting matrices is usually carried out by trial and error which is not a trivial problem. We proposed a efficient method using GA of finding weighting matrices for optimal control law. Thus, we prove the usefulness of proposed method to improve the stability of single machine-infinite bus with SVC system.

• Korean Management Science Review
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• v.20 no.1
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• pp.125-139
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• 2003

City gas is becoming an essential resource in households due to its convenience and low price in comparison to other energy sources. However, in order to prepare for the gas market to be saturated, many city gas companies must pursue customer satisfaction management and develop happy call systems for a promising solution. In the development of the happy call systems, the difficult problem is that we cannot contact all customers because of limited resources and calling efficiency in the call center, We should find best customers according to their value. This paper suggests a methodology for the selection of happy call customers when city 9as companies consider two strategies. First, they should launch a new business area. Second, they must attempt to prevent current customers from moving from city gas to other fuels. We will discover important attributes and derive rules of weighting for the attributes through an exploration study that affect customer satisfaction and preference. Through a simulation model, we will show how many customers will be selected by our methodology.

• 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.

• Journal of the Korea Institute of Building Construction
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• v.8 no.4
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• pp.61-69
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• 2008

The size of the construction projects become huge and complex, and the depth of excavation for the underground structures become deeper. Also the working area is not enough for loading materials and temporary facilities. This is the most case of recent construction projects in downtown area. Top-down is the most useful method for this kind of construction projects. Top-down construction method consists of supporting method, retaining wall type, foundation type and construction direction such as up-down or up-up. construction managers have to select sub-elements for top-down construction method in planning phase. This study is to suggest the sub-elements selection model for the top-down construction method, and the case study is conducted for evaluating this model.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.5C
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• pp.276-285
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• 2011

In this paper, we propose new cooperative precoder selection technique for interference limited MIMO networks. Our proposed method gives weighting to precoders in the codebook according to each precoder's performance priority. By applying our proposed method to precoder selection sequence, performance of entire system can be improved in terms of sumrate, stability, and feedback rate.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.253-256
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• 1997

This paper proposes a control strategy of position and force control in the same direction based on hybrid position/force control. In order to control position and force in the same direction, a weighting matrix is introduced instead of a selection matrix suggested by Raibert and Craig. The major part of the controller output comes from the position controller when a position control error is large, from the force controller when a position control error is large. The proposed algorithm is implemented by the simulation and experiment focusing on the peg-in-hole task where friction exist significantly and is not constant. It also adopts and event control scheme for more efficient performance.

• Journal of the military operations research society of Korea
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• v.30 no.1
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• pp.1-14
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• 2004

In this paper, we propose a new data-mining-based methodology for military occupational specialty assignment. The proposed methodology consists of two phases, feature selection and man-power assignment. In the first phase, the k-means partitioning algorithm and the optimal variable weighting algorithm are used to determine attribute weights. We address limitations of the optimal variable weighting algorithm and suggest a quadratic programming model that can handle categorical variables and non-contributory trivial variables. In the second phase, we present an integer programming model to deal with a man-power assignment problem. In the model, constraints on demand-supply requirements and training capacity are considered. Moreover, the attribute weights obtained in the first phase for each specialty are used to measure dissimilarity. Results of a computational experiment using real-world data are provided along with some analysis.