• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.1
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• pp.219-224
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• 2016

The vibration control performance of a semi-active damper connected to adjacent buildings subjected to seismic loads was investigated. The MR damper was used as a semi-active control device. A fuzzy logic control algorithm was used for effective control of the adjacent buildings connected to the MR damper. In the buildings control coupled with a MR damper, the response reduction of one building results in an increase in the response in another building. Because of these conflict characteristics, multi-objective optimization is required. Therefore, a fuzzy logic control algorithm for the control of a MR damper was optimized using a multi-objective genetic algorithm. Based on numerical analyses, the semi-active fuzzy control of MR damper for adjacent coupled buildings can provide good control performance.

• Journal of Korean Association for Spatial Structures
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• v.15 no.2
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• pp.105-112
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• 2015

A shared tuned mass damper (STMD) was proposed in previous research for reduction of dynamic responses of the adjacent buildings subjected to earthquake loads. A single STMD can provide similar control performance in comparison with two traditional TMDs. In previous research, a passive damper was used to connect the STMD with adjacent buildings. In this study, a smart magnetorheological (MR) damper was used instead of a passive damper to compose an adaptive smart STMD (ASTMD). Control performance of the ASTMD was investigated by numerical analyses. For this purpose, two 8-story buildings were used as example structures. Multi-input multi-output (MIMO) fuzzy logic controller (FLC) was used to control the command voltages sent to two MR dampers. The MIMO FLC was optimized by a multi-objective genetic algorithm. Numerical analyses showed that the ASTMD can effectively control dynamic responses of adjacent buildings subjected to earthquake excitations in comparison with a passive STMD.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.2C
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• pp.217-225
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• 2009

Tone injection scheme has been known as one of peak to average power ratio (PAPR) reduction methods deployable to multi-carrier system like orthogonal frequency division multiplexing (OFDM). The basic idea in tone injection scheme is to enforce the constellation size larger so that each of original constellation points is mapped into the preassigned distinct locations. According to the tone injection scheme, it increases symbol power highly induced inherently by expanding constellation to get optimal PAPR reduction. In the other hand, to get optimal power increase, the PAPR would be reduced insufficiently with limited tone injection signal. To withstand these problems, this paper consider the reduction of the PAPR and power increase problem simultaneously, Toward this, the tone injection scheme accomplished by employing the weighted sum genetic algorithm which has been utilized to solve multi-objective optimization problem (MOOP). The simulation results verifies that the proposed scheme can control the effective PAPR performance and alleviation of power increase flexibly by the weight value at the expense of relatively low complexity.

• 한국전산유체공학회:학술대회논문집
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• 2008.03b
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• pp.113-116
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• 2008

This work presents numerical optimization for design of staggered arrays of dimples printed on opposite surfaces of a cooling channel with a fast and elitist Non-Dominated Sorting of Genetic Algorithm (NSGA-II) of multi-objective optimization. As Pareto optimal front produces a set of optimal solutions, the trends of objective functions with design variables are predicted by hybrid multi-objective evolutionary algorithm. The problem is defined by three non-dimensional geometric design variables composed of dimpled channel height, dimple print diameter, dimple spacing and dimple depth to maximize heat transfer rate compromising with pressure drop. Twenty designs generated by Latin hypercube sampling were evaluated by Reynolds-averaged Navier-Stokes solver and the evaluated objectives were used to construct Pareto optimal front through hybrid multi-objective evolutionary algorithm. The optimum designs were grouped by k-mean clustering technique and some of the clustered points were evaluated by flow analysis. With increase in dimple depth, heat transfer rate increases and at the same time pressure drop also increases, while opposite behavior is obtained for the dimple spacing. The heat transfer performance is related to the vertical motion of the flow and the reattachment length in the dimple.

• Journal of Korea Water Resources Association
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• v.40 no.9
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• pp.677-685
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• 2007

The objective of this study is to evaluate the applicability of multi-objective genetic algorithm(MOGA) in order to calibrate the parameters of conceptual rainfall-runoff model, Tank model. NSGA-II, one of the most imitating MOGA implementations, is combined with Tank model and four multi-objective functions such as to minimize volume error, root mean square error (RMSE), high flow RMSE, and low flow RMSE are used. When NSGA-II is employed with more than three multi-objective functions, a number of Pareto-optimal solutions usually becomes too large. Therefore, selecting several preferred Pareto-optimal solutions is essential for stakeholder, and preference-ordering approach is used in this study for the sake of getting the best preferred Pareto-optimal solutions. Sensitivity analysis is performed to examine the effect of initial genetic parameters, which are generation number and Population size, to the performance of NSGA-II for searching the proper paramters for Tank model, and the result suggests that the generation number is 900 and the population size is 1000 for this study.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.1007-1014
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• 2015

An optimally designed six-phase induction motor (6PIM) is compared with an initial design induction motor having the same ratings. The Genetic Algorithm (GA) method is used for optimization and multi objective function is considered. Comparison of the optimum design with the initial design reveals that better performance can be obtained by a simple optimization method. Also in this paper each design of 6PIM, is simulated by MAXWELL_2D. The obtained simulation results are compared in order to find the most suitable solution for the specified application, considering the influence of each design upon the motor performance. Construction a 6PIM based on the information obtained from GA method has been done. Quality parameters of the designed motors, such as: efficiency, power losses and power factor measured and optimal design has been evaluated. Laboratory tests have proven the correctness of optimal design.

• Journal of Electrical Engineering and Technology
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• v.7 no.6
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• pp.948-953
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• 2012

The characteristics of an induction motor vary with the number of parameters and the performance relationship between the parameters also is implicit. In case of the induction motor design, we generally should estimate many objective physical quantities in the optimization procedure. In this article, the multi objective design optimization based on genetic algorithm is applied for the three phase induction motor. The efficiency, starting torque, and material cost are selected for the objectives. The validity of the design results is also clarified by comparison between calculated results and measured ones.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.26 no.2
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• pp.54-60
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• 2018

This paper contains the multi-mission scheduling optimization of UAV within a given operating time. Mission scheduling optimization problem is one of combinatorial optimization, and it has been shown to be NP-hard(non-deterministic polynomial-time hardness). In this problem, as the size of the problem increases, the computation time increases dramatically. So, we applied the genetic algorithm to this problem. For the application, we set the mission scenario, objective function, and constraints, and then, performed simulation with MATLAB. After 1000 case simulation, we evaluate the optimality and computing time in comparison with global optimum from MILP(Mixed Integer Linear Programming).

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.6 s.249
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• pp.698-704
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• 2006

This paper presents an electrode shape design method for the multi-mode sensors that could deteict the selected structural multiple modes. The structure used for this study is an isotropic cantilever beam type with a PVDF (polyvinylidene fluoride) which is bonded onto the structure as a sensor. The shape optimization problem is solved by using Genetic Algorithm (GA) with an appropriate objective function. The performance of analytical optimal shape sensor is compared with that of experimental work. The results show that the, obtained electrode shape sensors have good performance to detect the multiple vibration modes simultaneously.

• Transactions of Materials Processing
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• v.30 no.3
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• pp.125-133
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• 2021

In this study, response surface method (RSM), back propagation neural network (BPNN), and genetic algorithm (GA) were used for modeling and multi-objective optimization of the parameters of AA5052-H32 in incremental sheet forming (ISF). The goal of optimization is to determine the maximum forming angle and minimum surface roughness, while varying the production process parameters, such as tool diameter, tool spindle speed, step depth, and tool feed rate. A Box-Behnken experimental design (BBD) was used to develop an RSM model and BPNN model to model the variations in the forming angle and surface roughness based on variations in process parameters. Subsequently, the RSM model was used as the fitness function for multi-objective optimization of the ISF process the GA. The results showed that RSM and BPNN can be effectively used to control the forming angle and surface roughness. The optimized Pareto front produced by the GA can be utilized as a rational design guide for practical applications of AA5052 in the ISF process