• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.7
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• pp.694-704
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• 2011

In this paper, we present a design of a 5th order Chebyshev interdigital band-pass filter using inverter and susceptance slope parameter values obtained from EM simulated multi-port Y-parameters. The shifted length of the resonator is determined when the frequency of the transmission zero is separated far away from the center frequency. For the initial dimensions of the interdigital filter, the filter is decomposed into the individual resonators, and the dimensions are obtained using EM Simulation of the decomposed resonators. However, the interdigital filter with the dimensions determined from the EM simulation of the decomposed resonators shows slightly distorted response from the desired frequency response due to the coupling between non-adjacent resonators. To obtain a EM simulation dataset, EM simulation for this filter is carried out by parameter sweep with constant ratio for the initial values. In this dataset, it is determined the final values for the filter by optimization. The fabricated filter by PCB shows an upper-shift of center frequency of about 70 MHz, which was caused by permittivity changed and tolerance of fabrication.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.110-113
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• 2022

Nowadays, breaking through the conventional traffic signal control method based on mathematical optimization, artificial intelligence began to be used in the area. In response to this trend, many studies are ongoing to figure out how to utilize AI technology properly for traffic signal optimization. They just simply focus on which method will work well besides lots of machine learning techniques and abandon the reward function engineering. In many cases, the reward function consists of the average delay of the vehicles in the intersection. However, this may lead to AI's misunderstanding about the traffic signal control: what AI regards as a good situation may not be realistic. Even the reward function itself may not meet the service level. Therefore, this study analyzes the problems of previous reward functions and will suggest how to reward function can be enhanced.

• Wind and Structures
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• v.18 no.3
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• pp.253-265
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• 2014

The platform and floating structure of spar type offshore wind turbine systems should be designed in order for the 6-DOF motions to be minimized, considering diverse loading environments such as the ocean wave, wind, and current conditions. The objective of this study is to optimally design the platform and substructure of a 3MW spar type wind turbine system with the maximum postural stability in 6-DOF motions as well as the minimum material cost. Therefore, design variables of the platform and substructure were first determined and then optimized by a hydrodynamic analysis. For the hydrodynamic analysis, the body weight of the system was considered, and the ocean wave conditions were quantified to the wave forces using the Morison's equation. Moreover, the minimal number of computation analysis models was generated by the Design of Experiments (DOE), and the design variables of the platform and substructure were finally optimized by using a genetic algorithm with a neural network approximation.

• Journal of Mechanical Science and Technology
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• v.17 no.5
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• pp.654-667
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• 2003

This paper presents a consequence of the systematic approach to identify the aerodynamic parameters of an unmanned aerial vehicle (UAV) equipped with the automatic flight control system. A 3-2-1-1 excitation is applied for the longitudinal mode while a multi-step input is applied for lateral/directional excitation. Optimal time step for excitation is sought to provide the broad input bandwidth. A fully automated programmed flight test method provides high-quality flight data for system identification using the flight control computer with longitudinal and lateral/directional autopilots, which enable the separation of each motion during the flight test. The accuracy of the longitudinal system identification is improved by an additional use of the closed-loop flight test data. A constrained optimization scheme is applied to estimate the aerodynamic coefficients that best describe the time response of the vehicle. An appropriate weighting function is introduced to balance the flight modes. As a result, concurrent system models are obtained for a wide envelope of both longitudinal and lateral/directional flight maneuvers while maintaining the physical meanings of each parameter.

• Structural Engineering and Mechanics
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• v.12 no.5
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• pp.527-540
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• 2001

A new sort of learning algorithm named whole learning algorithm is proposed to simulate the nonlinear and dynamic behavior of RC members for the estimation of structural integrity. A mathematical technique to solve the multi-objective optimization problem is applied for the learning of the feedforward neural network, which is formulated so as to minimize the Euclidean norm of the error vector defined as the difference between the outputs and the target values for all the learning data sets. The change of the outputs is approximated in the first-order with respect to the amount of weight modification of the network. The governing equation for weight modification to make the error vector null is constituted with the consideration of the approximated outputs for all the learning data sets. The solution is neatly determined by means of the Moore-Penrose generalized inverse after summarization of the governing equation into the linear simultaneous equations with a rectangular matrix of coefficients. The learning efficiency of the proposed algorithm from the viewpoint of computational cost is verified in three types of problems to learn the truth table for exclusive or, the stress-strain relationship described by the Ramberg-Osgood model and the nonlinear and dynamic behavior of RC members observed under an earthquake.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.7
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• pp.673-679
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• 2015

In this study, the nondominated sorting genetic algorithm (NSGA-II) is used to obtain the optimized proportional-integral-derivative (PID) gain value that can quickly recover the motion of a quadcopter after a disturbance. Prior to PID control, the four-rotor quadcopter interval was defined using computational fluid dynamics (CFD). Through the definition of this model, the PID control algorithm was generated. To construct a response surface model, D-optimal programming was used for the generation of experimental points. For this purpose, a gain value that satisfies both the roll and altitude PID gain values is obtained. Using the NSGA-II, the gain value of shorten time of the quadcopter motion control can be optimized.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.19 no.2
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• pp.128-135
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• 2007

In response to anthropogenic global warming due to a buildup greenhouse gas, the effect of the air temperature on water temperature has been noticed. Therefore, effects have been made to build an air/water temperature relationship at three study regions using the data collected by the Ministry of the Maritime Affairs and Fisheries (MOMAF). The air/water relationship varies with time-scale and weekly time-scale was chosen for the study. The data were fitted to the S-shaped non-linear relationship, and the parameters for the S-curve were derived using a single-criteria multi-parameter optimization scheme. Separate regression curves were fitted to consider seasonal hysteresis at the Masan site. The study results support the S-shaped non-linear relationship is the best fit for the air/water relationship at the Korean coastal zone. This study will contribute to determine the future policy regarding water quality and ecosystem for the decision-driving organization.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5723-5743
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• 2018

The evolving internet-based services demand high-speed data transmission in conjunction with scalability. The next generation optical network has to exploit artificial intelligence and cognitive techniques to cope with the emerging requirements. This work proposes a novel way to solve the dynamic provisioning problem in optical network. The provisioning in optical network involves the computation of routes and the reservation of wavelenghs (Routing and Wavelength assignment-RWA). This is an extensively studied multi-objective optimization problem and its complexity is known to be NP-Complete. As the exact algorithms incurs more running time, the heuristic based approaches have been widely preferred to solve this problem. Recently the software-defined networking has impacted the way the optical pipes are configured and monitored. This work proposes the dynamic selection of path computation algorithms in response to the changing service requirements and network scenarios. A software-defined controller mechanism with a novel packet matching feature was proposed to dynamically match the traffic demands with the appropriate algorithm. A software-defined controller with Path Computation Element-PCE was created in the ONOS tool. A simulation study was performed with the case study of dynamic path establishment in ONOS-Open Network Operating System based software defined controller environment. A java based NOX controller was configured with a parent path computation element. The child path computation elements were configured with different path computation algorithms under the control of the parent path computation element. The use case of dynamic bulk path creation was considered. The algorithm selection method is compared with the existing single algorithm based method and the results are analyzed.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.43-52
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• 2021

In weapon assignment studies to defend against threats such as ballistic missiles and long range artillery, threat assessment was partially lacking in analysis of various threat attributes, and considering the threat characteristics of warheads, which are difficult to judge in the early flight stages, it is very important to apply more reliable optimal solutions than approximate solution using LP model, Meta heuristics Genetic Algorithm, Tabu search and Particle swarm optimization etc. Our studies suggest Generic Rule based threat evaluation and weapon assignment algorithm in the basis of various attributes of threats. First job of studies analyzes information on Various attributes such as the type of target, Flight trajectory and flight time, range and intercept altitude of the intercept system, etc. Second job of studies propose Rule based threat evaluation and weapon assignment algorithm were applied to obtain a more reliable solution by reflection the importance of the interception system. It analyzes ballistic missiles and long-range artillery was assigned to multiple intercept system by real time threat assessment reflecting various threat information. The results of this study are provided reliable solution for Weapon Assignment problem as well as considered to be applicable to establishing a missile and long range artillery defense system.

• Advances in nano research
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• v.11 no.6
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• pp.581-593
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• 2021

This model is proposed to describe the buckling behavior of Carbon Nanotubes (CNTs) embedded in an elastic medium taking into account the combined effects of the magnetic field, the temperature, the nonlocal parameter, the number of walls. Using Eringen's nonlocal elasticity theory, thin cylindrical shell theory and Van der Waal force (VdW) interactions, we develop a system of partial differential equations governing the buckling response of CNTs embedded on Winkler, Pasternak, and Kerr foundations in a thermal-magnetic environment. The pre-buckling stresses are obtained by applying airy's stress function and an adjacent equilibrium criterion. To estimate the nonlocal critical buckling load of CNTs under the simultaneous effects of the magnetic field, the temperature change, and the number of walls, an optimization technique is proposed. Furthermore, analytical formulas are developed to obtain the buckling behavior of SWCNTs embedded in an elastic medium without taking into account the effects of the nonlocal parameter. These formulas take into account VdW interactions between adjacent tubes and the effect of terms involving differences in tube radii generally neglected in the derived expressions of the critical buckling load published in the literature. Most scientific research on modeling the effects of magnetic fields is based on beam theories, this motivation pushes me to develop a cylindrical shell model for studying the effect of the magnetic field on the static behavior of CNTs. The results show that the magnetic field has significant effects on the static behavior of CNTs and can lead to slow buckling. On the other hand, thermal effects reduce the critical buckling load. The findings in this work can help us design of CNTs for various applications (e.g. structural, electrical, mechanical and biological applications) in a thermal and magnetic environment.