• Journal of Electrical Engineering and Technology
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• v.12 no.4
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• pp.1417-1426
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• 2017

Power system analysis, Non-Convex Economic Dispatch (NED) is considered as an open and demanding optimization problem. Despite the fact that realistic ED problems have non-convex cost functions with equality and inequality constraints, conventional search methods have not been able to effectively find the global answers. Considering the great potential of meta-heuristic optimization techniques, many researchers have started applying these techniques in order to solve NED problems. In this paper, a new and efficient approach is proposed based on imperialist competitive algorithm (ICA). The proposed algorithm which is named multi-operator ICA (MuICA) merges three operators with the original ICA in order to simultaneously avoid the premature convergence and achieve the global optimum answer. In this study, the proposed algorithm has been applied to different test systems and the results have been compared with other optimization methods, tending to study the performance of the MuICA. Simulation results are the confirmation of superior performance of MuICA in solving NED problems.

• Structural Engineering and Mechanics
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• v.43 no.6
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• pp.771-794
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• 2012

This paper presents a multi-objective evolutionary algorithm for combinatorial optimisation and applied for design optimisation of fiber reinforced composite structures. The proposed algorithm closely follows the implementation of Pareto Archive Evolutionary strategy (PAES) proposed in the literature. The modifications suggested include a customized neighbourhood search algorithm in place of mutation operator to improve intensification mechanism and a cross over operator to improve diversification mechanism. Further, an external archive is maintained to collect the historical Pareto optimal solutions. The design constraints are handled in this paper by treating them as additional objectives. Numerical studies have been carried out by solving a hybrid fiber reinforced laminate composite cylindrical shell, stiffened composite cylindrical shell and pressure vessel with varied number of design objectives. The studies presented in this paper clearly indicate that well spread Pareto optimal solutions can be obtained employing the proposed algorithm.

• Journal of Korea Multimedia Society
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• v.21 no.8
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• pp.858-863
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• 2018

In this paper, we propose and implement a multi-level convolutional neural network (CNN) algorithm to identify the sexually explicit and lewdness of various image files, and verify its effectiveness by using unauthorized image files generated in the actual military. The proposed algorithm increases the accuracy by applying the convolutional artificial neural network step by step to minimize classification error between similar categories. Experimental data have categorized 20,005 images in the real field into 6 authorization categories and 11 non-authorization categories. Experimental results show that the overall detection rate is 99.51% for the image files. In particular, the excellence of the proposed algorithm is verified through reducing the identification error rate between similar categories by 64.87% compared with the general CNN algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.7
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• pp.1263-1271
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• 2001

There are two methods in blood pressure measurement ; Invasive methode and Non-invasive method. The Invasive methode can get the 띠cod pressure measurement but, patient feel uncomfortable. So Non-invasive methode used generally. The Oscillometric method is typical Non-Invasive method. This method is commonly used to measure BP in electric sphygmomanometer and has various algorithm. In this paper it is described about a algorithm, it controls, determinates the cuff pressure, and fillers the measured BP data. This system can interface with PC(personal computer) by RS-232 and save the measured data in PC. This system deflates the cuff pressure by Solenoid valve. The main algorithm are oscillometric and maximum amplitude algorithm(MAA). MAA has various measured oscillation, it depends on patient's age, height, weight and arm circumference size. In this paper proposed system can measure Systolic BP, Diastolic BP, and Mean BP using Interpolation, Auto Reinflation algorithm.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.4
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• pp.265-276
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• 2004

Genetic Algorithm(GA), that is shown stable performance to find an optimal solution, has been used as a method of solving large-scaled optimization problems with complex constraints in various applications. Since it takes so much time to execute a long computation process for iterative evolution and adaptation. In this paper, a hardware-based adaptive GA was proposed to reduce the serious computation time of the evolutionary process and to improve the accuracy of convergence to optimal solution. The proposed GA, based on steady-state model among continuos generation model, performs an adaptive mutation process with consideration of the evolution flow and the population diversity. The drawback of the GA, premature convergence, was solved by the proposed adaptation. The Performance improvement of convergence accuracy for some kinds of problem and condition reached to 5-100% with equivalent convergence speed to high-speed algorithm. The proposed adaptive GAP(Genetic Algorithm Processor) was implemented on FPGA device Xilinx XCV2000E of EHW board for face recognition.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.1052-1057
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• 1993

A scara type Direct Drive Arm(DDA) with two degrees-of-freedom is designed and implemented. The direct drive motor is used to furnish large torque to reduce the modeling error by the gear and chains. To control the DDA, a multiprocessor control structure with multirate dynamic control algorithm is designed. In the control algorithm, the dynamics of system is used to calculate the nominal control torque and the feedback controls are calculated with a parallel processing algorithm for each joint. The laboratory experiments on Hong-Ik DDA by dynamic control algorithm are presented and compared to that of PID control algorithm. This result shows that the proposed controller guarantees small trajectory error and stability. With this research, Hong-Ik DDA is expected to be utilized as A basic tool for robotics and control engineering.

• IEMEK Journal of Embedded Systems and Applications
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• v.7 no.5
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• pp.247-253
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• 2012

This paper presents sensor network based autonomous vehicle system using a proposed image processing algorithm. The proposed image processing algorithm consists of pre-processing and five-stage image processing: coordinate calculation, driving area decision, line segment calculation, steeling decision, and acceleration decision. We evaluate the performance of the proposed algorithm on both straight road and curved road. Experimental results indicate that the proposed algorithm works well for autonomous vehicles. However, control accuracy of the proposed algorithm decreases as speed is increasing.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.1
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• pp.54-64
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• 1997

In this paper, a method of dynamic modeling and a dynamic control of a mobile robot are presented to show the superiority of the dynamic control comparing to the PD control. This dynamic model is derived from the cartesian coordinates using lagrange equations. Based upon the derived dynamic model, we implemented the dynamic control of the mobile robot using the computed torque method. Time varying non-linear friction terms are not incroporated in this dynamic model. Instead, those are considered as disturbances. This uncertainty in dynamic model of mobile robot is compensated by the outer loop controller using PD algorithm. The validity of this model and the control algorithm are confirmed through the experiments, where the dynamic control algorithm demonstrated robust velocity tracking performance against the unmodeled non-linear frictions. The superiority of this algorithm is demonstrated by comparing to classical PD control algorithm.

• Genomics & Informatics
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• v.9 no.3
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• pp.134-135
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• 2011

DNA chips are used for experiments on genes and provide useful information that could be further analyzed. Using the data extracted from the DNA chips to find useful patterns or information has become a very important issue. In this paper, we explain the application developed for classifying DNA chip data using a classification method based on the Particle Swarm Optimization (PSO) algorithm. Considering that DNA chip data is extremely large and has a fuzzy characteristic, an algorithm that imitates the ecosystem such as the PSO algorithm is suitable to be used for analyzing such data. The application enables researchers to customize the PSO algorithm parameters and see detail results of the classification rules.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.5
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• pp.1221-1229
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• 1996

This paper proposes a heuristic algorithm for low power implementation of combinational circuits. Selecting an input variable for a given function, the proposed algorithm performs Shannon exansion with respect to the variable to reduce the number of gates in the subcircuit realizing the coffactor function, reducting the power dissipation of the implemented circuit. experimental results for the MCNC benchmarks show that the proposed algorithm is effective by generating the circuits consuming the power 48.9% less on the average, when compared to the previous algorithm based on precomputation logic.