• 한국자동차공학회논문집
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• 제21권4호
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• pp.16-22
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• 2013

In this study, we propose the method of optimally changing material of BIW for minimizing weight while satisfying vehicle requirements on static stiffness. First, we formulate a material selection optimization problem. Next, we establish the CAE procedure of evaluating static stiffness. Then, to enhance the efficiency of design work, we integrate and automate the established CAE procedure using a commercial process integration and design optimization (PIDO) tool, PIAnO. For effective optimization, we adopt the approach of metamodel based approximate optimization. As a sampling method, an orthogonal array (OA) is used for selecting sampling points. The response values are evaluated at the sampling points and then these response values are used to generate a metamodel of each response using the linear polynomial regression (PR) model. Using the linear PR model, optimization is carried out an evolutionary algorithm (EA) that can handle discrete design variables. Material optimization result reveals that the weight is reduced by 44.8% while satisfying all the design constraints.

• 한국자동차공학회논문집
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• 제21권5호
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• pp.8-14
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• 2013

In this study, we propose the method of optimally selecting material of front pillar (A-pillar) and package tray for minimizing weight while satisfying vehicle requirements on static stiffness and dynamic stiffness. First, we formulate a material selection optimization problem. Next, we establish the CAE procedure of evaluating static stiffness and dynamic stiffness. Then, to enhance the efficiency of design work, we integrate and automate the established CAE procedure using a commercial process integration and design optimization (PIDO) tool, PIAnO. For effective optimization, we adopt the approach of metamodel based approximate optimization. As a sampling method, an orthogonal array (OA) is used for selecting sampling points. The response values are evaluated at the sampling points and then these response values are used to generate a metamodel of each response using the radial basis function regression (RBFr). Using the RBFr models, optimization is carried out an evolutionary algorithm that can handle discrete design variables. Material optimization result reveals that the weight is reduced by 49.8% while satisfying all the design constraints.

• Journal of Electrical Engineering and Technology
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• 제2권4호
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• pp.413-419
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• 2007

The optimal power flow (OPF) problem was introduced by Carpentier in 1962 as a network constrained economic dispatch problem. Since then, it has been intensively studied and widely used in power system operation and planning. In the past few decades, many stochastic optimization methods such as Genetic Algorithm (GA), Evolutionary Programming (EP), and Particle Swarm Optimization (PSO) have been applied to solve the OPF problem. In particular, PSO is a newly proposed population based stochastic optimization algorithm. The main idea behind it is based on the food-searching behavior of birds and fish. Compared with other stochastic optimization methods, PSO has comparable or even superior search performance for some hard optimization problems in real power systems. Nowadays, some modifications such as breeding and selection operators are considered to make the PSO superior and robust. In this paper, we propose the Modified PSO (MPSO), in which the mutation operator of GA is incorporated into the conventional PSO to improve the search performance. To verify the optimal solution searching ability, the proposed approach has been evaluated on an IEEE 3D-bus test system. The results showed that performance of the proposed approach is better than that of the standard PSO.

• International Journal of Aeronautical and Space Sciences
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• 제12권2호
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• pp.163-174
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• 2011

Task assignments of multiple unmanned aerial vehicles (UAVs) are examined. The phrase "task assignment" comprises the decision making procedures of a UAV group. In this study, an on-line decentralized task assignment algorithm is proposed for an autonomous UAV group. The proposed method is divided into two stages: an order optimization stage and a communications and negotiation stage. A genetic algorithm and negotiation strategy based on one-to-one communication is adopted for each stage. Through the proposed algorithm, decentralized task assignments can be applied to dynamic environments in which sensing range and communication are limited. The performance of the proposed algorithm is verified by performing numerical simulations.

• International Journal of Computer Science & Network Security
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• 제23권7호
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• pp.39-48
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• 2023

Breast cancer screening makes extensive utilization of mammography. Even so, there has been a lot of debate with regards to this application's starting age as well as screening interval. The deep learning technique of transfer learning is employed for transferring the knowledge learnt from the source tasks to the target tasks. For the resolution of real-world problems, deep neural networks have demonstrated superior performance in comparison with the standard machine learning algorithms. The architecture of the deep neural networks has to be defined by taking into account the problem domain knowledge. Normally, this technique will consume a lot of time as well as computational resources. This work evaluated the efficacy of the deep learning neural network like Visual Geometry Group Network (VGG Net) Residual Network (Res Net), as well as inception network for classifying the mammograms. This work proposed optimization of ResNet with Teaching Learning Based Optimization (TLBO) algorithm's in order to predict breast cancers by means of mammogram images. The proposed TLBO-ResNet, an optimized ResNet with faster convergence ability when compared with other evolutionary methods for mammogram classification.

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 1997년도 춘계학술발표회논문집(1)
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• pp.502-507
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• 1997

As a maintenance optimization project to improve the safety of Wolsong NPP (Nuclear Power Plant), reliability of diesel generators are estimated based on the operating experience, and improvement options are suggested. A reliability measure is suggested for the estimation of reliability for standby safety systems to reflect availability. It is assessed that the reliability of diesel generators can be much improved if the suggested improvement options are implemented.

• 제어로봇시스템학회논문지
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• 제21권11호
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• pp.1003-1007
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• 2015

Depth calibration is a procedure for finding the conversion function that maps disparity data from a depth-sensing camera to actual distance information. In this paper, we present an optimal depth calibration method for Kinect$^{TM}$ sensors based on an experimental design and convex optimization. The proposed method, which utilizes multiple measurements from only two points, suggests a simplified calibration procedure. The confidence ellipsoids obtained from a series of simulations confirm that a simpler procedure produces a more reliable calibration function.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 추계학술대회 논문집 전력기술부문
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• pp.198-200
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• 2006

This paper presents a development of an educational simulator of particle swarm optimization (PSO) and application for solving the test functions and economic dispatch (ED) problems with nonsmooth cost functions. A particle swarm optimization is one of the most powerful methods for solving global optimization problems. It is a population-based search algorithm and searches in parallel using a group of particles similar to other AI-based heuristic optimization techniques. In developed simulator, lecturers and students can select the functions for simulation and set the parameters that have an influence on PSO performance. To improve searching capability for ED problems, a crossover operation is proposed to the position update of each individual (CR-PSO). To verify the feasibility of CR-PSO method, numerical studies have been performed for two different sample systems. The proposed CR-PSO method outperforms other algorithms in solving ED problems.

• Computers and Concrete
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• 제7권3호
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• pp.221-237
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• 2010

In this study 72 different high strength concrete (HSC) mixes were produced according to the Taguchi design of experiment method. The specimens were divided into four groups based on the range of their compressive strengths 40-60, 60-80, 80-100 and 100-125 MPa. Each group included 18 different concrete mixes. The slump and air-content values of each mix were measured at the production time. The compressive strength, splitting tensile strength and water absorption properties were obtained at 28 days. Using this data the Genetic Programming technique was used to construct models to predict mechanical properties of HSC based on its constituients. These models, together with the cost data, were then used with a Genetic Algorithm to obtain an HSC mix that has minimum cost and at the same time meets all the strength and workability requirements. The paper describes details of the experimental results, model development, and optimization results.

• Journal of Radiation Protection and Research
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• 제46권1호
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• pp.1-7
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• 2021

Background: The use of computed tomography (CT) device has increased in the past few decades in Japan. Dose optimization is strongly required in pediatric CT examinations, since there is concern that an unreasonably excessive medical radiation exposure might increase the risk of brain cancer and leukemia. To accelerate the process of dose optimization, continual assessment of the dose levels in actual hospitals and medical facilities is necessary. This study presents organ dose estimation using pediatric cerebral CT scans in the Kyushu region, Japan in 2012 and the web-based calculator, WAZA-ARI (https://waza-ari.nirs.qst.go.jp). Materials and Methods: We collected actual patient information and CT scan parameters from hospitals and medical facilities with more than 200 beds that perform pediatric CT in the Kyushu region, Japan through a questionnaire survey. To estimate the actual organ dose (brain dose, bone marrow dose, thyroid dose, lens dose), we divided the pediatric population into five age groups (0, 1, 5, 10, 15) based on body size, and inputted CT scan parameters into WAZA-ARI. Results and Discussion: Organ doses for each age group were obtained using WAZA-ARI. The brain dose, thyroid dose, and lens dose were the highest in the Age 0 group among the age groups, and the bone marrow and thyroid doses tended to decrease with increasing age groups. All organ doses showed differences among facilities, and this tendency was remarkable in the young group, especially in the Age 0 group. This study confirmed a difference of more than 10-fold in organ doses depending on the facility and CT scan parameters, even when the same CT device was used in the same age group. Conclusion: This study indicated that organ doses varied widely by age group, and also suggested that CT scan parameters are not optimized for children in some hospitals and medical facilities.