• Proceedings of the Korean Information Science Society Conference
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• 2007.10c
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• pp.367-370
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• 2007

In this paper, we concentrate on the mask design problem for optical micro-lithography. The pre-distorted mask is obtained by minimizing the error between the designed output image and the projected output image. We use the particle swarm optimization(PSO) and fuzzy system to insure that the resulting images are identical to the desired image. Our method has good performance for the iteration number by an experiment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.5
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• pp.1638-1653
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• 2014

A sequential optimization algorithm (SOA) for resource allocation in a cyclic-prefixed single-carrier cognitive relay system is proposed in this study. Both subcarrier pairing (SP) and power allocation are performed subject to a primary user interference constraint to minimize the mean squared error of frequency-domain equalization at the secondary destination receiver. Under uniform power allocation at the secondary source and optimal power allocation at the secondary relay, the ordered SP is proven to be asymptotically optimal in maximizing the matched filter bound on the signal-to-interference-plus-noise ratio. SOA implements the ordered SP before power allocation optimization by decoupling the ordered SP from the power allocation. Simulation results show that SOA can optimize resource allocation efficiently by significantly reducing complexity.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1990.10a
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• pp.95-100
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• 1990

An optimization method has been developed to find the minimum weight design of steel building structures which consist of the commercially available discrete sections. In this study, an emphasis was particularly placed on the practical applicability of optimization algorithm in engineering practice. The structure Is optimized through element optimization under the element level constraints first and then, if there is any violation of structural level constraints, it is adequately compensated by the constraint error correction vector obtained through the sensitivity analysis. A scaling procedure is introduced for the problems of large violated displacement constraint. The oscillation control in the objective function is also discussed. By dividing the available H-sections into two groups based on their section characteristics, much improved relationships between section variables were obtained and used efficiently in searching the optimum section in the section table.

• Proceedings of the KIEE Conference
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• 1999.07a
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• pp.253-255
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• 1999

In this paper, a shape optimization algorithm of superconducting magnet using finite element method is presented. Since the superconductor loses its superconductivity over the critical magnetic field and critical current density, this material property should be taken into account in the design process. Trial and error approach of repeating the change of the design variables costs much time and it sometimes does not guarantee an optimal design. This paper presents a systematic and efficient design algorithm for the superconducting magnet. We employ the sensitivity analysis based on finite element formulation. As for optimization algorithm, the inequality constraint for the superconducting state is removed by modifying the objective function and the nonlinear equality constraint of constant volume is satisfied by the gradient projection method. This design algorithm is applied to an optimal design problem of a solenoid air-cored superconducting magnet that has a design objective of the maximum energy storage.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.6
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• pp.686-691
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• 2011

This study is concerned with the identification of fuzzy models. To address the optimization of fuzzy model, we proposed an improved space search evolutionary algorithm (ISSA) which is realized with the combination of space search algorithm and Gaussian mutation. The proposed ISSA is exploited here as the optimization vehicle for the design of fuzzy models. Considering the design of fuzzy models, we developed a hybrid identification method using information granulation and the ISSA. Information granules are treated as collections of objects (e.g. data) brought together by the criteria of proximity, similarity, or functionality. The overall hybrid identification comes in the form of two optimization mechanisms: structure identification and parameter identification. The structure identification is supported by the ISSA and C-Means while the parameter estimation is realized via the ISSA and weighted least square error method. A suite of comparative studies show that the proposed model leads to better performance in comparison with some existing models.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.101-110
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• 2022

Histopathological analysis of biopsy specimens is still used for diagnosis and classifying the brain tumors today. The available procedures are intrusive, time consuming, and inclined to human error. To overcome these disadvantages, need of implementing a fully automated deep learning-based model to classify brain tumor into multiple classes. The proposed CNN model with an accuracy of 92.98 % for categorizing tumors into five classes such as normal tumor, glioma tumor, meningioma tumor, pituitary tumor, and metastatic tumor. Using the grid search optimization approach, all of the critical hyper parameters of suggested CNN framework were instantly assigned. Alex Net, Inception v3, Res Net -50, VGG -16, and Google - Net are all examples of cutting-edge CNN models that are compared to the suggested CNN model. Using huge, publicly available clinical datasets, satisfactory classification results were produced. Physicians and radiologists can use the suggested CNN model to confirm their first screening for brain tumor Multi-classification.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.4
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• pp.1075-1089
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• 2024

In this paper, the optimizations of multi-hop cooperative molecular communication (CMC) system in cylindrical anomalous-diffusive channel in three-dimensional enviroment are investigated. First, we derive the performance of bit error probability (BEP) of CMC system under decode-and-forward relay strategy. Then for achieving minimum average BEP, the optimization variables are detection thresholds at cooperative nodes and destination node, and the corresponding optimization problem is formulated. Furthermore, we use conjugate gradient (CG) algorithm to solve this optimization problem to search optimal detection thresholds. The numerical results show the optimal detection thresholds can be obtained by CG algorithm, which has good convergence behaviors with fewer iterations to achieve minimized average BEP compared with gradient decent algorithm and Bisection method which are used in molecular communication.

• Journal of Computational Design and Engineering
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• v.3 no.3
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• pp.179-190
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• 2016

A kind of modified epoxy resin sheet molding compounds of the impeller has been designed. Through the test, the non-metal impeller has a better environmental aging performance, but must do the waterproof processing design. In order to improve the stability of the impeller vibration design, the influence of uncertainty factors is considered, and a multi-objective robust optimization method is proposed to reduce the weight of the impeller. Firstly, based on the fluid-structure interaction, the analysis model of the impeller vibration is constructed. Secondly, the optimal approximate model of the impeller is constructed by using the Latin hypercube and radial basis function, and the fitting and optimization accuracy of the approximate model is improved by increasing the sample points. Finally, the micro multi-objective genetic algorithm is applied to the robust optimization of approximate model, and the Monte Carlo simulation and Sobol sampling techniques are used for reliability analysis. By comparing the results of the deterministic, different sigma levels and different materials, the multi-objective optimization of the SMC molding impeller can meet the requirements of engineering stability and lightweight. And the effectiveness of the proposed multi-objective robust optimization method is verified by the error analysis. After the SMC molding and the robust optimization of the impeller, the optimized rate reached 42.5%, which greatly improved the economic benefit, and greatly reduce the vibration of the ventilation system.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2006.07a
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• pp.345-345
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• 2006

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.10a
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• pp.647-648
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• 2009