• Journal of Communications and Networks
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• 제7권4호
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• pp.489-498
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• 2005

For better performance over a noisy channel, mobile wireless networks transmit packets with forward error correction (FEC) code to recover corrupt bits without retransmission. The static determination of the FEC code size, however, degrades their performance since the evaluation of the underlying channel state is hardly accurate and even widely varied. Our measurements over a wireless sensor network, for example, show that the average bit error rate (BER) per second or per minute continuously changes from 0 up to $10^{-3}$. Under this environment, wireless networks waste their bandwidth since they can't deterministically select the appropriate size of FEC code matching to the fluctuating channel BER. This paper proposes an adaptive FEC technique called adaptive FEC code control (AFECCC), which dynamically tunes the amount of FEC code per packet based on the arrival of acknowl­edgement packets without any specific information such as signal to noise ratio (SNR) or BER from receivers. Our simulation experiments indicate that AFECCC performs better than any static FEC algorithm and some conventional dynamic hybrid FEC/ARQ algorithms when wireless channels are modeled with two-state Markov chain, chaotic map, and traces collected from real sensor networks. Finally, AFECCC implemented in sensor motes achieves better performance than any static FEC algorithm.

• 대한전기학회논문지:전력기술부문A
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• 제53권10호
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• pp.529-535
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• 2004

Load forecasting is essential in the electricity market for the participants to manage the market efficiently and stably. A wide variety of techniques/algorithms for load forecasting has been reported in many literatures. These techniques are as follows: multiple linear regression, stochastic time series, general exponential smoothing, state space and Kalman filter, knowledge-based expert system approach (fuzzy method and artificial neural network). These techniques have improved the accuracy of the load forecasting. In recent 10 years, many researchers have focused on artificial neural network and fuzzy method for the load forecasting. In this paper, we propose an algorithm of a hybrid load forecasting method using fuzzy linear regression and general exponential smoothing and considering the sensitivities of the temperature. In order to consider the lower load of weekends and Monday than weekdays, fuzzy linear regression method is proposed. The temperature sensitivity is used to improve the accuracy of the load forecasting through the relation of the daily load and temperature. And the normal load of weekdays is easily forecasted by general exponential smoothing method. Test results show that the proposed algorithm improves the accuracy of the load forecasting in 1996.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 B
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• pp.794-796
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• 1999

본 논문에서는 3상 유도전동기의 속도를 제어하는데 기존 제어기의 문제점을 해결하고 최적화하기 위해서 유전자 알고리즘을 이용한 하이브리드 퍼지 -PID(HFPID) 제어기를 고안하고, 이에 대한 파라미터 설정 방법을 제안한다. 유도전동기의 제어는 지연시간이 길고, 비선형성이 강하며, 부하변동이 잦은 프로세스이기 때문에, 기존의 제어방식으로는 만족할만한 결과를 얻을 수 없다. 제안한 하이브리드 퍼지-PID 제어기는 PID 제어기의 장점인 과도기의 우수성과 퍼지 제어기의 장점인 정상기의 우수성을 퍼지 변수로 결합시켜 설계한다. 이 제어기에 유전자 알고리즘을 적용하여 최적의 퍼지 및 PID 파라미터를 설정하다. 그리고 이 제어기를 3상 유도전동기의 속도 제어에 응용한다. 또한 속도오차에 대한 룩업 표를 만들어 온라인 실시간 제어를 가능하게 한다. 이상의 과정을 3상 유도전동기에서 컴퓨터 시뮬레이션 하였다. 시뮬레이션 결과를 비교해 볼 때, 하이브리드 퍼지-PID 제어기는 기존의 제어기 보다 전동기의 속도 및 토크성분 전류 둥의 특성에서 우수한 성능을 보였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권1호
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• pp.1-20
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• 2018

Service composition in the Inter-Cloud raises new challenges that are caused by the different Quality of Service (QoS) requirements of the users, which are served by different geo-distributed Cloud providers. This paper aims to explore how to select and compose such services while considering how to reach high efficiency on cost and response time, low network latency, and high reliability across multiple Cloud providers. A new hybrid multi-objective evolutionary algorithm to perform the above task called LS-NSGA-II-DE is proposed, in which the differential evolution (DE) algorithm uses the adaptive mutation operator and crossover operator to replace the those of the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) to get the better convergence and diversity. At the same time, a Local Search (LS) method is performed for the Non-dominated solution set F{1} in each generation to improve the distribution of the F{1}. The simulation results show that our proposed algorithm performs well in terms of the solution distribution and convergence, and in addition, the optimality ability and scalability are better compared with those of the other algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권7호
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• pp.2960-2976
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• 2018

The limited storage and computing capacity hinder the development of cognitive radio ad hoc networks (CRAHNs). To solve the problem, a new paradigm of cloud-based CRAHN has been proposed, in which a CRAHN will make use of the computation and storage resources of the cloud. This paper envisions an integrated CRAHN-cloud network architecture. In this architecture, some cognitive radio users (CUs) who satisfy the required metrics could perform as mobile gateway candidates to connect other ordinary CUs with the cloud. These mobile gateway candidates are dynamically clustered according to different related metrics. Cluster head and time-to-live value are determined in each cluster. In this paper, the gateway advertisement and discovery issues are first addressed to propose a hybrid gateway discovery mechanism. After that, a QoS-based gateway selection algorithm is proposed for each CU to select the optimal gateway. Simulations are carried out to evaluate the performance of the overall scheme, which incorporates the proposed clustering and gateway selection algorithms. The results show that the proposed scheme can achieve about 11% higher average throughput, 10% lower end-to-end delay, and 8% lower packet drop fractions compared with the existing scheme.

• 대한전자공학회논문지TC
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• 제45권5호
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• pp.21-29
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• 2008

본 논문은 IEEE802.11n 시스템의 반송파 주파수 옵셋 추정 알고리즘을 제안한다. IEEE802.11n 시스템은 다중 송수신 안테나 시스템이므로 종래의 단일 송수신 안테나 시스템에 적용되는 알고리즘과는 다르게 다중 수신부에서 적용 가능한 결합 기법을 고려하여 적용하여야 한다. 따라서 본 논문에서는 IEEE802.11n 과 같은 다중 수신 안테나 시스템에서 적용 가능한 수신기 결합 구조의 반송파 주파수 옵셋 추정 알고리즘을 제안하고, 제안하는 선택적 결합 반송파 주파수 옵셋 추정 알고리즘이 종래의 알고리즘보다 SNR 10dB에서 채널 B 인 경우에 1/10, 채널 D 인 경우에 1/2 의 MSE 오류로 추정이 가능함을 확인하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 심포지엄 논문집 정보 및 제어부문
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• pp.207-209
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• 2007

In this paper, we introduce a genetic optimization of fuzzy set-fuzzy model using successive tuning method to carry out the model identification of complex and nonlinear systems. To identity we use genetic alrogithrt1 (GA) sand C-Means clustering. GA is used for determination the number of input, the seleced input variables, the number of membership function, and the conclusion inference type. Information Granules (IG) with the aid of C-Means clustering algorithm help determine the initial paramters of fuzzy model such as the initial apexes of the, membership functions in the premise part and the initial values of polyminial functions in the consequence part of the fuzzy rules. The overall design arises as a hybrid structural and parametric optimization. Genetic algorithms and C-Means clustering are used to generate the structurally as well as parametrically optimized fuzzy model. To identify the structure and estimate parameters of the fuzzy model we introduce the successive tuning method with variant generation-based evolution by means of GA. Numerical example is included to evaluate the performance of the proposed model.

• 대한산업공학회지
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• 제33권2호
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• pp.201-212
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• 2007

Genetic algorithms (GAs) are very useful methods for global search and have been applied to various optimization problems. They have two kinds of important search mechanisms, crossover and mutation. Because the performance of GAs depends on these operators, a large number of operators have been developed for improving the performance of GAs. Especially, many researchers have been more interested in a crossover operator than a mutation operator. The reason is that a crossover operator is a main search operator in GAs and it has a more effect on the search performance. So, we also focus on a crossover operator. In this paper we first investigate the drawback of various crossovers, especially subtour-based crossovers and then introduce a new crossover operator to avoid such drawback and to increase efficiency. Also we compare it with several crossover operators for symmetric traveling salesman problem (STSP) for showing the performance of the proposed crossover. Finally, we introduce an efficient simple hybrid genetic algorithm using the proposed operator and then the quality and efficiency of the obtained results are discussed.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2008년도 추계학술대회A
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• pp.801-805
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• 2008

Today, hydraulic systems play an important role in modern industry for the reasons that hydraulic actuator systems take many advantages over other technologies with high durability and the ability to produce large forces at high speeds. In recent years, electro-hydraulic actuator systems, which combine electric and hydraulic technology into a compact unit, have been adapted to a wide variety of force, speed and torque requirements. Moreover these systems resolve energy consumption and noise problems characteristic existed in the conventional hydraulic systems. Therefore, these systems have a wide range application fields especially in an excavator. So the purpose of this paper is to demonstrate efficiency of the energy saving and present some control algorithms which apply to electro-hydraulic actuator system in the bucket of the excavator. Experiments are carried out to verify the effectiveness of the proposed system with various external loads as in real working conditions.

• Journal of Power Electronics
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• 제11권4호
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• pp.479-489
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• 2011

The bidirectional dc-dc converter, being the interface between Energy Storage Element (ESE) and DC bus, is an essential component of the power management system for vehicle applications including electric vehicle (EV), hybrid electric vehicle (HEV), and fuel cell vehicle (FCV). In this paper, a novel multiphase bidirectional dc-dc converter interfacing with battery to supply and absorb the electric energy in the FCV system was studied with the help of real time digital simulator (RTDS). The mathematical models of fuel cell, battery and dc-dc converter were derived. A power management strategy was developed and first simulated in RTDS. A Power Hardware-In-the-Loop (PHIL) simulation using RTDS is then presented. The main challenge of this PHIL is the requirement for a highly dynamic bidirectional Simulation-Stimulation (Sim-Stim) interface. This paper describes three different interface algorithms. The closed-loop stability of the resulting PHIL system is analyzed in terms of time delay and sampling rate. A prototype bidirectional Sim-Stim interface is designed to implement the PHIL simulation.