• Journal of Communications and Networks
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• 제12권4호
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• pp.375-381
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• 2010

A flooding attack, such as DoS or Worm, can be easily created or even downloaded from the Internet, thus, it is one of the main threats to servers on the Internet. This paper presents an online real-time network response system, which can determine whether a LAN is suffering from a flooding attack within a very short time unit. The detection engine of the system is based on the incremental mining of fuzzy association rules from network packets, in which membership functions of fuzzy variables are optimized by a genetic algorithm. The incremental mining approach makes the system suitable for detecting, and thus, responding to an attack in real-time. This system is evaluated by 47 flooding attacks, only one of which is missed, with no false positives occurring. The proposed online system belongs to anomaly detection, not misuse detection. Moreover, a mechanism for dynamic firewall updating is embedded in the proposed system for the function of eliminating suspicious connections when necessary.

• 전자공학회논문지 IE
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• 제46권2호
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• pp.7-10
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• 2009

본 논문은 진화 하드웨어 시스템의 엔진으로 사용하기 위한 유전알고리즘의 하드웨어 구현 및 실험과 분석에 대한 연구이다. 진화 하드웨어는 응용에 따라 동작되어지는 환경에 적응하여 동적이면서 자동적으로 자기의 구조를 바꿀 수 있는 능력을 가진 하드웨어로써 재구성 가능한 하드웨어 부분과 유전알고리즘과 같은 진화 연산을 하는 부분으로 구성 되어 있다. 유전알고리즘은 실시간 응용 부분 등에 있어서 하드웨어로 구현하는 것이 속도 면에서 유리하다. 하드웨어로 처리하는 것이 병렬성, 파이프라인 처리, 그리고 함수 사용 부분 등에 있어 소프트웨어의 단점을 보완하여 이득이 있기 때문이다. 본 논문에서는 유전알고리즘을 하드웨어로 구현하여, 몇 가지 예제에 대하여 실험을 하고 실험 결과를 분석하여 그 구조가 유리함을 보였다.

• The Korean Journal of Ecology
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• 제27권1호
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• pp.21-26
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• 2004

Understanding farmer household and community management of crop diversity is necessary in order to effectively strengthen the local plant genetic resources management system in Vietnam, Assessment and management for distribution of farmer's cultivars of rice, taro and tropical tree species were conducted in four different agro-ecological zones in Vietnam using participatory approaches, focus surveys, diversity fairs, agro-morphological field trials, isozyme analysis to understand why Vietnamese farmers grow diverse types of these crop cultivars, when and where these crops cultivars are grown and how farmers maintain and use them. Results showed significant differences in the extent, distribution and use pattern crop cultivars diversity in contrasting environments and between community farmer households. Seed system is an important role in the access and use of diversity in eco-geographical regions.

• 제어로봇시스템학회논문지
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• 제4권5호
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• pp.624-629
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• 1998

Evolutionary computation techniques can solve search problems using simulated evolution based on the ‘survival of the fittest’. Recently, the genetic programming (GP) which evolves computer programs using the genetic algorithm was introduced. In this paper, the genetic programming technique is used in order to design a rule based controller consisting of condition-action rules for an unknown system. No a priori knowledge about the structure of the controller is needed. Representation of a solution, functions and terminals in GP are analyzed, and a method of constructing a fuzzy logic controller using the obtained rule based controller is described. A simulation example using a nonlinear system shows the validity and efficiency of the proposed method.

• 제어로봇시스템학회논문지
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• 제5권7호
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• pp.876-882
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• 1999

It is difficult to determine the feeding rate of coagulant in the water treatment process, due to nonlinearity, multivariables and slow response characteristics, etc. To deal with this difficulty, the genetic-fuzzy system was used in determining the feeding rate of the coagulant. The genetic algorithms are excellently robust in complex optimization problems. Since it uses randomized operators and searches for the best chromosome without auxiliary informations from a population consists of codings of parameter set. To apply this algorithms, we made the lookup table and membership function from the actual operation data of the water treatment process. We determined optimum dosages of coagulant(LAS) by the fuzzy operation, and compared it with the feeding rate of the actual operation data.

• 동력기계공학회지
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• 제7권3호
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• pp.29-34
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• 2003

Genetic algorithm is a optimization technique based on the mechanics of natural selection and natural genetics. Global optimum solution can be obtained efficiently by operations of reproduction, crossover and mutation in genetic algorithm. The authors developed a computer program which can optimize marine propulsion shafting by using binary-coded genetic algorithm and modal analysis method. In order to confirm the effectiveness of the developed computer program, we apply the program to a optimum design problem which is to obtain optimum diameters of intermediate shaft and propeller shaft in marine propulsion shafting. Objective function is to minimize total mass of shafts and constraints are that torsional vibration stresses of shafts in marine propulsion shafting can not exceed the permissible torsional vibration stresses of the ship classification society. The computational results by the program were compared with those of conventional design technique.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 학술대회 논문집 전문대학교육위원
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• pp.141-145
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• 2001

In this paper, model reference PID genetic controller was proposed in order to overcome the difficulty of reflecting control performance required in the overall control system and defects of the adaptation performance in the PID genetic controller. The proposed controller comprised Inner feedback loop consisting of the PID controller and plant, and outer loop consisting of an genetic algorithm which was designed for tuning a parameter of the controller. A reference model was used for design criteria of a PID controller which characterizes and quantizes the control performance required in the overall control system. Tuning parameter of the controller is performed by the genetic algorithm. The performance of proposed algorithm was verified through experiment for the DC servo motor.

• Journal of Ubiquitous Convergence Technology
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• 제2권1호
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• pp.40-50
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• 2008

The problem of assigning customers to satellite channels is a difficult combinatorial optimization problem and is NP-complete. For this combinatorial optimization problem, standard optimization methods take a large computation time and so genetic algorithms (GA) and ant colony optimization (ACO) can be used to obtain the best and/or optimal assignment of customers to satellite channels. In this paper, we present a comparative study of GA and ACO to this problem. Various issues related to genetic algorithms approach to this problem, such as solution representation, selection methods, genetic operators and repair of invalid solutions are presented. We also discuss an ACO for this problem. In ACO methodology, three strategies, ACO with only ranking, ACO with only max-min ant system (MMAS), and ACO with both ranking and MMAS, are considered. A comparison of these two approaches (i,e., GA and ACO) with the standard optimization method is presented to show the advantages of these approaches in terms of computation time.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.71.2-71
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• 2001

This paper deals with nonlinear system modelling using neural network and genetic algorithm. Application of neural network to control and identification is actively studied because of their approximating ability of nonlinear function. It is important to design the neural network with optimal structure for minimum error and fast response time. Genetic algorithm is getting more popular nowadays because of their simplicity and robustness. In this paper, We optimize neural network structure using genetic algorithm. The genetic algorithm uses binary coding for neural network structure and search for optimal neural network structure of minimum error and response time. Through extensive simulation, Optimal neural network structure is shown to be effective for ...

• Journal of Positioning, Navigation, and Timing
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• 제11권2호
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• pp.99-107
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• 2022

Urban Air Mobility (UAM) such as a drone taxi is one of the future transportations that have recently been attracting attention. Along with the construction of an urban terminal, an accurate landing system for UAM is also essential. However, in urban environments, reliable Global Navigation Satellite Systems (GNSS) signals cannot be received due to obstacles such as high-rise buildings which causes multipath and non-line of sight signal. Thus, the positioning result in urban environments from the GNSS signal is unreliable. Consequently, we propose the Ultra-Wideband (UWB) network to assist the soft landing of UAM on a vertiport. Since the positioning performance of UWB network depends on the layout of UWB anchors, it is necessary to optimize the layout of UWB anchors. In this paper, we propose a two-steps genetic algorithm that consists of binary genetic algorithm involved multi objectives fitness function and integer genetic algorithm involved robust solution searching fitness function in order to optimize taking into account Fresnel hole effects.