• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2011년도 춘계학술대회 논문집
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• pp.1311-1312
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• 2011

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1028-1032
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• 2004

In order to prevent machine tool feed slide system from transient vibrations during operations, machine tool designers usually adopt some typical design solutions; box-in-box typed feed slides, optimizing moving body for minimum weight and dynamic compliance, and so on. Despite all efforts for optimizing design, a feed drive system may experience severe transient vibrations during high-speed operation if its feed rate control is unsuitable. A rough feed rate curve having discontinuity in its acceleration profile causes a serious vibration problem in the feed slides system. This paper presents a feed rate optimization of a ball screw driven machine tool feed slide system for its minimum vibration. Firstly, a ball screw feed drive system was mathematically modeled as a 6-degree-of-freedom lumped parameter system. Next, a feed rate optimization of the system was carried out for minimum vibrations. The main idea of the feed rate optimization is to find out the most appropriate smooth acceleration profile with jerk continuity. A genetic algorithm was used in this feed rate optimization

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권6호
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• pp.2504-2526
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• 2016

Wireless sensors are always deployed in brutal environments, but as we know, the nodes are powered only by non-replaceable batteries with limited energy. Sending, receiving and transporting information require the supply of energy. The essential problem of wireless sensor network (WSN) is to save energy consumption and prolong network lifetime. This paper presents a new communication protocol for WSN called Dynamical Threshold Control Algorithm with three-parameter Particle Swarm Optimization and Ant Colony Optimization based on residual energy (DPA). We first use the state of WSN to partition the region adaptively. Moreover, a three-parameter of particle swarm optimization (PSO) algorithm is proposed and a new fitness function is obtained. The optimal path among the CHs and Base Station (BS) is obtained by the ant colony optimization (ACO) algorithm based on residual energy. Dynamical threshold control algorithm (DTCA) is introduced when we re-select the CHs. Compared to the results obtained by using APSO, ANT and I-LEACH protocols, our DPA protocol tremendously prolongs the lifecycle of network. We observe 48.3%, 43.0%, and 24.9% more percentages of rounds respectively performed by DPA over APSO, ANT and I-LEACH.

• Journal of Computing Science and Engineering
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• 제9권2호
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• pp.39-50
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• 2015

Genetic algorithm (GA) and particle swarm optimization (PSO) are two excellent approaches to multimodal optimization problems. However, slow convergence or premature convergence readily occurs because of inappropriate and inflexible evolution. In this paper, a novel optimization algorithm with a flexible grid optimization (FGO) is suggested to provide adaptive trade-off between exploration and exploitation according to the specific objective function. Meanwhile, a uniform agents array with adaptive scale is distributed on the gird to speed up the calculation. In addition, a dominance centroid and a fitness center are proposed to efficiently determine the potential guides when the population size varies dynamically. Two types of subregion division strategies are designed to enhance evolutionary diversity and convergence, respectively. By examining the performance on four benchmark functions, FGO is found to be competitive with or even superior to several other popular algorithms in terms of both effectiveness and efficiency, tending to reach the global optimum earlier. Moreover, FGO is evaluated by applying it to a parameter decision in a least squares support vector machine (LS-SVM) to verify its practical competence.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2004년도 추계학술대회 논문집
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• pp.321-325
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• 2004

Linear motor feed drive systems have been broadly used in machine tools or precision automatic feed systems. Recently, modem machine tools require high speed and high precision feed drive system to achieve high productivity. Unfortunately, a feed drive system, even though it was optimum designed, may experience severe transient vibrations during high-speed operation if its feed rate control is unsuitable. A rough feed rate curve having discontinuity in its acceleration profile causes a serious vibration problem in the feed slides system. This paper presents a feed rate optimization of a machine tool feed slide system, which is driven by a linear motor, for its minimum vibrations. Firstly, a 4-degree-of-freedom lumped parameter model is proposed for the vibration analysis of a linear motor driven machine tool feed drive system. Next, a feed rate optimization of the feed slide is carried out for minimum vibrations. The feed rate curve optimization strategy is to find out the most appropriate acceleration profile with jerk continuity. Of course, the optimized feed rate should approximate to the desired one as possible. A genetic algorithm with variable penalty function was used in this feed rate optimization.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2004년도 추계학술대회논문집
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• pp.962-966
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• 2004

Ball screw feed drive systems have been broadly used in machine tools or precision automatic feed systems. Recently, modern machine tools require high speed and high precision and drive system to achieve high productivity. Unfortunately, a feed drive system, even though it was optimum designed, may experience severe transient vibrations during high-speed operation if its feed rate control is unsuitable. A rough feed rate curve having discontinuity in its acceleration profile causes a serious vibration problem in the feed slide system. This paper presents a feed rate optimization of a machine tool feed slide system, which is driven by a ball screw, for its minimum vibrations. Firstly, a 6-degree-of-freedom lumped parameter model was proposed for the vibration analysis of a ball screw driven machine tool feed drive system. Next, a feed rate optimization of the feed slide was carried out for minimum vibrations. The feed rate curve optimization strategy is to find out the most appropriate acceleration profile having finite jerk. Of course, the optimized feed rate should approximate to the desired one as possible. A genetic algorithm with variable penalty function was used in this feed rate optimization.

• 한국산업융합학회 논문집
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• 제25권1호
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• pp.121-129
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• 2022

With the recent increase in international trade volume the trade volume through ships is also continuously increasing. The treatment of ballast water goes through the following five steps, samples are taken and analyzed at each step, and samples are obtained using a suction pump. These suction pumps have low efficiency and thus need to be improved. In this study, it is to optimize the form of the impeller which affects directly improvements of performance to determine the capacity of suction pump and to fulfill the purpose of this research. To do it, we have carried out parametric design as an input variable, geometric form for the impeller. By conducting the flow analysis for the optimum form, it has confirmed the value of improved results and achieved the purpose to study in this paper. It has selected the necessary parameter for optimizing the form of the pump impeller and analyzed the property using experiment design. And it can reduce the factor of parameter for local optimization from findings to analyze the property of form parameter. To perform MOGA(Multi-Objective Genetic Algorithm) it has generated response surface using parameters for local optimization and conducts the optimization using multi-objective genetic algorithm. with created experiment cases, it has performed the computational fluid dynamics with model applying the optimized impeller form and checked that the capacity of the pump was improved. It could verify the validity concerning the improvement of pump efficiency, via optimization of pump impeller form which is suggested in this study.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2018년도 학술발표회
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• pp.448-448
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• 2018

In this study, the regression models (Load ESTimator and eight-parameter model) were evaluated to estimate instantaneous pollutant loads under various criteria and optimization methods. As shown in the results, LOADEST commonly used in interpolating pollutant loads could not necessarily provide the best results with the automatic selected regression model. It is inferred that the various regression models in LOADEST need to be considered to find the best solution based on the characteristics of watersheds applied. The recently developed eight-parameter model integrated with Genetic Algorithm (GA) and Gradient Descent Method (GDM) were also compared with LOADEST indicating that the eight-parameter model performed better than LOADEST, but it showed different behaviors in calibration and validation. The eight-parameter model with GDM could reproduce the nitrogen loads properly outside of calibration period (validation). Furthermore, the accuracy and precision of model estimations were evaluated using various criteria (e.g., $R^2$ and gradient and constant of linear regression line). The results showed higher precisions with the $R^2$ values closed to 1.0 in LOADEST and better accuracy with the constants (in linear regression line) closed to 0.0 in the eight-parameter model with GDM. In hence, based on these finding we recommend that users need to evaluate the regression models under various criteria and calibration methods to provide the more accurate and precise results for pollutant load estimations.

• 품질경영학회지
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• 제21권1호
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• pp.96-107
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• 1993

In parameter design Taguchi analyzed a statistic which he called signal-to-noise(SN) ratio by using the experimental design technique. However he gave no justification for using SN ratios in the optimization procedure of parameter design. In this paper we discuss the validity of such SN ratios as proper statistics to be analyzed in parameter design. Moreover, using the real empirical data we examine the appropriateness of SN ratios, and we explain how transformation technique can be applied in parameter design as an alternative method of analysis.

• 한국항공우주학회지
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• 제40권3호
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• pp.215-221
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• 2012

본 논문에서는 추적-회피 게임에서 추적자의 추적성능을 향상시키기 위한 최적화 기법을 소개한다. 제한된 공간상에서 추적자는 도망자를 빠른 시간 내에 찾아내고 잡기 위해 확률맵을 생성하고 그 확률정보를 토대로 탐색한다. 추적자는 기존 global-max와 local-max의 장점을 취한 hybrid 추적방식을 사용하는데 이 추적방식은 global-max와 local-max 성향을 조절하는 가중치를 갖는다. 따라서 상황별 최적의 가중치를 찾기 위해 에피소드 매개변수 최적화 알고리즘을 제안하였다. 이 알고리즘은 가중치에 대한 다수의 추적-회피 게임 에피소드를 반복적으로 수행하는 동안 강화학습을 통해 보상을 누적한 후 해당 가중치의 평균보상을 최대화 하는 방향으로 황금분할법을 사용하여 최적의 가중치를 찾는다. 이 최적화 기법을 이용하여 여러 상황별 최적 추적정책을 찾기 위해 도망자 수와 공간의 크기를 변화시켜가며 각각 최적화를 수행하였고 그 결과를 분석하였다.