• Journal of Powder Materials
• /
• v.11 no.5
• /
• pp.399-411
• /
• 2004

Crack generation during die compaction and distortion during sintering have been critical problems for the conventional pressing and sintering process. Until now, trial and error approach with engineers' industrial experiences has been only solution to protect the crack generation and distortion. However, with complexity in shape and process it is very difficult to design process conditions without CAE analysis. We developed the exclusive CAE software (PMsolver/Compaction) for die compaction process. The accuracy of PMsolver is verified by comparing the finite element simulation results with experimental results. The simplified procedures to find material properties are proposed and verified with iron based powder and tungsten carbide powder. Based on the accurate simulation result by PMsolver, the optimal process conditions are designed to get uniform density distribution in a powder compact after die compaction process by using a derivative based optimization scheme. In addition, the effect of non-uniform density distribution in a powder compact on distortion during sintering is shown in case of the fabrication of tungsten carbide insert.

• ETRI Journal
• /
• v.32 no.3
• /
• pp.395-405
• /
• 2010

A novel multiclassifier system (MCS) strategy is proposed and applied to a text-dependent speaker verification task. The presented scheme optimizes the linear combination of classifiers on an on-line basis. In contrast to ordinary MCS approaches, neither a priori distributions nor pre-tuned parameters are required. The idea is to improve the most accurate classifier by making use of the incremental information provided by the second classifier. The on-line multiclassifier optimization approach is applicable to any pattern recognition problem. The proposed method needs neither a priori distributions nor pre-estimated weights, and does not make use of any consideration about training/testing matching conditions. Results with Yoho database show that the presented approach can lead to reductions in equal error rate as high as 28%, when compared with the most accurate classifier, and 11% against a standard method for the optimization of linear combination of classifiers.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.11 no.9
• /
• pp.827-832
• /
• 2001

In this paper, we propose a sequentially optimization method for fuzzy inference system using fuzzy equalization and linguistic hedge. The fuzzy equalization does not require the usual learning step for generating fuzy rules. However, it is too sensitive for the given input-output data set. So, we adopt a sequential scheme which sequentially optimizes the fuzzy inference system. Here, the parameters of fuzzy membership function obtained from the fuzzy equalization are optimized by the genetic algorithm, and then they are also modified to increase the performance index using the linguistic hedge. Finally, we applied it to rice taste data and got better results than previous ones.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.35S no.4
• /
• pp.67-75
• /
• 1998

In general, Evoluationary Algorithm(EAs) are refered to as methods of population-based optimization. And EAs are considered as very efficient methods of optimal sytem design because they can provice much opportunity for obtaining the global optimal solution. This paper presents a co-evolution scheme of artifical neural networks, which has two different, still cooperatively working, populations, called as a host popuation and a parasite population, respectively. Using the conventional generatic algorithm the host population is evolved in the given environment, and the parastie population composed of schemata is evolved to find useful schema for the host population. the structure of artificial neural network is a diagonal recurrent neural netork which has self-feedback loops only in its hidden nodes. To find optimal neural networks we should take into account the structure of the neural network as well as the adaptive parameters, weight of neurons. So we use the genetic algorithm that searches the structure of the neural network by the co-evolution mechanism, and for the weights learning we adopted the evolutionary stategies. As a results of co-evolution we will find the optimal structure of the neural network in a short time with a small population. The validity and effectiveness of the proposed method are inspected by applying it to the stabilization and position control of the invered-pendulum system. And we will show that the result of co-evolution is better than that of the conventioal genetic algorithm.

• Journal of Communications and Networks
• /
• v.11 no.4
• /
• pp.390-405
• /
• 2009

Wireless sensor networks (WSNs) are envisioned to facilitate information gathering for various applications and depending on the application types they may require certain quality of service (QoS) guarantee for successful and guaranteed event perception. Therefore, QoS in WSNs is an important issue and two most important parameters that hinder the goal of guaranteed event perception are time-sensitive and reliable delivery of gathered information, while a minimum energy consumption is desired. In this paper, we propose an energy-aware, multi-constrained and multipath QoS provisioning mechanism for WSNs based on optimization approach. Hence, a detailed analytical analysis of reliability, delay and energy consumption is presented to formulate the optimization problem in an analytical way. A greedy algorithm is proposed to achieve the desired QoS guarantee while keeping the energy consumption minimum. Also, a simple but efficient retransmission mechanism is proposed to enhance the reliability further, while keeping the delay within delay bound. Simulation results demonstrate the effectiveness of our scheme.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.30 no.4
• /
• pp.313-318
• /
• 2017

This study performs the structural analysis and the optimum design of a vibrating metal damper to absorb vibration energy. Unlike other dampers such as rubber bearing, friction or viscose dampers, the present vibrating metal damper utilizes the plastic deformation of a steel and its associated hysteresis phenomenon to reduce vibrations of structures. To optimize this vibrating metal damper, it is important to obtain plastic deformation through the damper. To achieve this, the shape optimization method is developed and applied to find out optimal envelopes of the metal damper. Depending on the parameterization scheme, some novel optimal shapes can be found.

• ETRI Journal
• /
• v.37 no.3
• /
• pp.471-479
• /
• 2015

Traditional designs of cognitive radio (CR) focus on maximizing system throughput. In this paper, we study the joint overlay and underlay power allocation problem for orthogonal frequency-division multiple access-based CR. Instead of maximizing system throughput, we aim to maximize system energy efficiency (EE), measured by a "bit per Joule" metric, while maintaining the minimal rate requirement of a given CR system, under the total power constraint of a secondary user and interference constraints of primary users. The formulated energy-efficient power allocation (EEPA) problem is nonconvex; to make it solvable, we first transform the original problem into a convex optimization problem via fractional programming, and then the Lagrange dual decomposition method is used to solve the equivalent convex optimization problem. Finally, an optimal EEPA allocation scheme is proposed. Numerical results show that the proposed method can achieve better EE performance.

• 한국방재학회:학술대회논문집
• /
• 2008.02a
• /
• pp.723-726
• /
• 2008

It is not always easy to estimate the parameters in hydrologic models due to insufficient hydrologic data when hydraulic structures are designed or water resources plan are established, uncertainty analysis, therefore, are inevitably needed to examine reliability for the estimated results. With regard to this point, this study applies a Bayesian Markov Chain Monte Carlo scheme to the NWS-PC rainfall-runoff model that has been widely used, and a case study is performed in Soyang Dam watershed in Korea. The NWS-PC model is calibrated against observed daily runoff, and thirteen parameters in the model are optimized as well as posterior distributions associated with each parameter are derived. The Bayesian Markov Chain Monte Carlo shows a improved result in terms of statistical performance measures and graphical examination. The patterns of runoff can be influenced by various factors and the Bayesian approaches are capable of translating the uncertainties into parameter uncertainties. One could provide against an expected runoff event by utilizing information driven by Bayesian methods. Therefore, the rainfall-runoff analysis coupled with the uncertainty analysis can give us an insight in evaluating flood risk and dam size in a reasonable way.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.12 no.1
• /
• pp.98-106
• /
• 2007

This paper represent improved on-line turn off angle control schemes for switched reluctance motors based on current control. For the purpose of finding the optimal commutation switching angle point with improved controller, it is utilized turn on and turn off position calculation with inductance vs. current vs. not linkage analysis method. The goal of proposed paper is the maximization of the energy conversion per stroke and torque ripple reduction and obtaining approximately flat-topped current waveform. The proposed control scheme is demonstrated simulation and on a prototype experimental system.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2005.11a
• /
• pp.159-163
• /
• 2005

A dynamic vibration absorber using the Zener's model has been taken into account with respect to frequency response characteristics. The concept of the tuned mass damper with a single degree of freedom has been well applied for many industrial fields, because many researchers have extensively studied various basic characteristics, performance and optimization methods for long time. The Zener's model has an additional spring, which is connected between a damper and a mass, while the tuned mass damper with a single degree of freedom consists of a mass, a spring and a damper connected in parallel. In previous works, the basic performance and characteristics of the Zoner's model as a dynamic vibration absorber have not been investigated. In this study, the frequency response characteristics according to the parameter change of the Zener's model have been described. In order to find the optimum value of several parameters, we use iterative scheme with three dimensional frequency response diagram by MATLAB programming. Present results shows the Zener's model can give more good damping performance than the simple tuned mass damper, and the numerical of optimization method should be developed for the efficient vibration absorbtion.