• Journal of applied mathematics & informatics
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• v.28 no.3_4
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• pp.597-610
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• 2010

For a class of nonlinear bilevel programming problems in which the follower's problem is linear, the paper develops a genetic algorithm based on the optimality conditions of linear programming. At first, we denote an individual by selecting a base of the follower's linear programming, and use the optimality conditions given in the simplex method to denote the follower's solution functions. Then, the follower's problem and variables are replaced by these optimality conditions and the solution functions, which makes the original bilevel programming become a single-level one only including the leader's variables. At last, the single-level problem is solved by using some classical optimization techniques, and its objective value is regarded as the fitness of the individual. The numerical results illustrate that the proposed algorithm is efficient and stable.

• Journal of Electrical Engineering and Technology
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• v.7 no.1
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• pp.17-22
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• 2012

Lagrangian relaxation is the most widely adopted method for solving unit commitment (UC) problems. It consists of two steps: dual optimization and primal feasible solution construction. The dual optimization step is crucial in determining the overall performance of the solution. This paper intends to evaluate two dual optimization methods - one based on subgradient (SG) and the other based on the cutting plane. Large-scale UC problems with hundreds of thousands of variables and constraints have been generated for evaluation purposes. It is found that the evaluated SG method yields very promising results.

• Journal of Electrical Engineering and information Science
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• v.2 no.6
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• pp.191-196
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• 1997

Fuzzy clustering has been playing an important role in solving many problems. Fuzzy c-Means(FCM) algorithm is most frequently used for fuzzy clustering. But some fixed point of FCM algorithm, know as Tucker's counter example, is not a reasonable solution. Moreover, FCM algorithm is impossible to perform the on-line learning since it is basically a batch learning scheme. This paper presents unsupervised learning networks as an attempt to improve shortcomings of the conventional clustering algorithm. This model integrates optimization function of FCM algorithm into unsupervised learning networks. The learning rule of the proposed scheme is a result of formal derivation based on the gradient descent procedure of a fuzzy objective function. Using the result of formal derivation, two algorithms of fuzzy cluster analysis, the batch learning version and on-line learning version, are devised. They are tested on several data sets and compared with FCM. The experimental results show that the proposed algorithms find out the reasonable solution on Tucker's counter example.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.621-624
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• 2021

최근 빅데이터에 대한 관심이 높아지면서 분석을 위해 필요한 데이셋의 표준화에 대한 중요성이 강조되고 있다. 데이터 표준화를 위해서는 업무 처리에 필요한 모든 데이터의 명명 규칙을 규정하고 그 기준에 따라 표준 명칭을 부여하여야 한다. 본 연구에서는 사전을 기반으로 하는 항목명 표준화 시스템을 제안하였다. 제안한 시스템은 공개된 표준단어사전을 활용하여 유의어를 포함한 참조 사전을 구축하고 이를 기반으로 표준사전을 구축하여 표준 항목명을 제공한다. 기 구축된 데이터셋의 항목명을 입력하거나 사용자가 원하는 새로운 항목명을 입력하면 항목명 표준화 시스템은 표준화된 한글 항목명과 영문 항목명, 그리고 테이블 설계에 사용하는 영문 약어명을 출력한다. 본 연구에서 제안한 시스템을 테이블 설계에 활용하거나 기 구축된 데이터셋을 표준화하는데 적용하면 일관된 데이터 해석이나 관리가 가능할 것으로 기대된다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.10
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• pp.1830-1834
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• 2008

At the present day, devices for measurement and control of data by wireless based computer have been generalized. The devices with low cost and high performance have been spotlighted. If Zigbee communication solution is used in dangerous places and places that can not in use wire communication, computer can process data without limitation. Zigbee communication solution is effective in power consumption as compared with RF or bluetooth and can use battery. System cost of Zigbee also is very low, so can install lots of nodes. The system made in this paper transmit by wireless many LMCs(Laser Measuring Control) of wireless transmission system for distance measurement and many slave Zigbee to a master Zigbee.

• Journal of the Korea Society of Computer and Information
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• v.24 no.1
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• pp.137-143
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• 2019

As the performance of computers increases, the use of deep learning, which has faced technical limitations in the past, is becoming more diverse. In many fields, deep learning has contributed to the creation of added value and used on the bases of more data as the application become more divers. The process for obtaining a better performance model will require a longer time than before, and therefore it will be necessary to find an optimal model that shows the best performance more quickly. In the artificial neural network modeling a tuning process that changes various elements of the neural network model is used to improve the model performance. Except Gride Search and Manual Search, which are widely used as tuning methods, most methodologies have been developed focusing on heuristic algorithms. The heuristic algorithm can get the results in a short time, but the results are likely to be the local optimal solution. Obtaining a global optimal solution eliminates the possibility of a local optimal solution. Although the Brute Force Method is commonly used to find the global optimal solution, it is not applicable because of an infinite number of hyper parameter combinations. In this paper, we use a statistical technique to reduce the number of possible cases, so that we can find the global optimal solution.

• Proceeding of EDISON Challenge
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• 2017.03a
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• pp.625-627
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• 2017

Cardiovascular disease is the leading cause of death in America [1]. This kind of situation leads researcher to find out how to analyze the disease without using a living human heart. Computer simulation is the solution. Based on the existed clinical data and mathematical formulas from the journals, we can simulate a human heart activity using a computer. Moreover, we can also use the existed biological data in our simulation program, such as CellML (Cell Markup Language) [2].

• Journal of Electrical Engineering and Technology
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• v.7 no.1
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• pp.64-68
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• 2012

In this paper, a design method for minimizing the cogging torque of an Interior Permanent Magnet Motor (IPM) is proposed based on a hybrid algorithm. The suggested optimization algorithm is based on a combination of the Response Surface Method (RSM) and Simplex Method. The results show that the proposed method provides improved characteristics compared to the conventional methods, such as a shorter calculation time and the acquisition of a more correct solution.

• Nonlinear Functional Analysis and Applications
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• v.27 no.3
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• pp.679-689
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• 2022

In this paper, we establish sufficient conditions for the existence and uniqueness of solution for a class of initial boundary value problems with Dirichlet condition in regard to a category of fractional-order partial differential equations. The results are established by a method based on the theorem of Lax Milligram.

• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.149-154
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• 2023

Internet of Things (IoT) is now spreading everywhere. It's the technology of every person's need so we can't step back from IoT but we can secure it as it is spreading quickly so it has greater chances of danger and being misused. There is an urgent need to make IoT devices secure from getting cracked or hacked. A lot of methods had tried and still trying to mitigate IoT security issues. In this paper Blockchain is going to be the solution of most of the IoT issues or problems. We have discussed or highlighted security issues with centralized IoT and then provided solution of such security challenges through the use of blockchain because is based on a decentralized technology that is hard to modify or update.