• Journal of Power System Engineering
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• v.9 no.4
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• pp.194-201
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• 2005

In this paper, we propose an adaptive mechanism based on humoral immune algorithm and neural network identifier technique. It is also applied for an autonomous guided vehicle (AGV) system. When the immune algorithm is applied to the PID controller, there exists the case that the plant is damaged due to the abrupt change of PID parameters since the parameters are almost adjusted randomly. To slove this problem, we use the neural network identifier technique for modeling the plant humoral immune algorithm (HIA) which performs the parameter tuning of the considered model, respectively. Finally, the experimental results for control of steering and speed of AGV system illustrate the validity of the proposed control scheme. Also, these results for the proposed method show that it has better performance than other conventional controller design method such as PID controller.

• Proceedings of the Korean Information Science Society Conference
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• 2001.04a
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• pp.754-756
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• 2001

컴퓨터 사용증가와 함께 컴퓨터 바이러스 또한 증가하고 있다. 바이러스 검사 프로그램은 바이러스의 특정 문자열(signature)을 찾아 문자열 검색도구와 프로세스의 행동을 모니터링 하는 감시도구(general purpose monitor)의 두 가지 형태가 있으며, 각각은 미 발견 바이러스에 대한 취약성과 시스템 오버헤드를 단점으로 가지고 있다. 또한, 최근에 제안된 면역 시스템은 계산 복잡도나 시스템 구성면에서 지나친 부담을 가지고 있다. 본 논문에서는 바이러스들의 행위를 추출 할 수 있도록 하기 위하여, 언어 압축 알고리즘을 이용하여 바이러스 행동 패턴을 추출하는 방법을 고안하였고, 몇 가지 바이러스를 이용하여 실험해 보았다. 그 결과 실제 학습에 이용한 바이러스가 아니더라도 유사한 동작을 하는 바이러스에 대해서는 면역성을 가질 수 있었다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.4B
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• pp.566-575
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• 2010

In recent, artificial immune system has become an important research direction in the anomaly detection of networks. The conventional artificial immune systems are usually based on the negative selection that is one of the computational models of self/nonself discrimination. A main problem with self and non-self discrimination is the determination of the frontier between self and non-self. It causes false positive and false negative which are wrong detections. Therefore, additional functions are needed in order to detect potential anomaly while identifying abnormal behavior from analogous symptoms. In this paper, we design novel network attack detection and response schemes based on artificial immune system, and evaluate the performance of the proposed schemes. We firstly generate detector set and design detection and response modules through adopting the interaction between dendritic cells and T-cells. With the sequence of buffer occupancy, a set of detectors is generated by negative selection. The detection module detects the network anomaly with a set of detectors and generates alarm signal to the response module. In order to reduce wrong detections, we also utilize the fuzzy number theory that infers the degree of threat. The degree of threat is calculated by monitoring the number of alarm signals and the intensity of alarm occurrence. The response module sends the control signal to attackers to limit the attack traffic.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04a
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• pp.847-849
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• 2002

인공면역시스템에서 중요한 특징중의 하나는 지속적으로 변화하는 환경에서 자기(self)의 유동적인 패턴을 동적으로 학습하고 비자기(non-self)에 대한 새로운 패턴을 예측하는데 있다. 본 논문은 자기적 용(self-adaptation)의 인공면역체계 특성을 기반으로하여 설계된 dynamics(동적 클론선택 알고리즘, dynamic clonal selection algorithm)의 역할을 논한다. 시스템의 세가지 중요한 변수인 자기내성 기간(Tolerisation Period). 연역 반응 임계값(activation threshold). 수명(life span)에 따라 변화하는 dynamics의 성능을 네트워크 침입에서 흔히 발견되는 시나리오를 모의실험하여 평가한다

• ETRI Journal
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• v.9 no.3
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• pp.74-85
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• 1987

In this paper, a new kind of dual tone multifrequency receiver(DTMFR) is proposed, in which detection is made in terms of the partial correlation(PARCOR) coefficients for efficient DTMF signal detection against both temporary decoding errors by crosstalks possibly coming from adjoint telephone lines during transmission and so-called digit simulation by background voice or noise signals during interdigit period. A simulation study on the behaviour of PARCOR coefficients for tone signals and non-signals has been performed in order to provide the rationale on the feasibility of the proposed DTMFR algorithm. Based upon simulation results, a more refined detection strategy as an example is presented and explained together with the corresponding decision logic.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.5
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• pp.19-28
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• 2000

It is not so easy to control the wheeled mobile robot because of some causes like non-holonomic constraints. To overcome these problems, a controller that PD system is combined with fuzzy process is composed of several steps that have each separate algorithm and niche search algorithm and immune algorithm is applied partly. Output term set is changed by search that is performed to get optimal elements and then the rule base is also reformed. The fitness for the altered system is estimated and the surplus elements are removed. After the adjustment of output term set and rule base is finished, input and output membership functions is tuned.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.29 no.1
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• pp.399-404
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• 2005

In this paper, An immunized PID(I-PID) controller based on cell mediated immune response is proposed to improve the control performance of the controller with PID scheme. And it is applied to the vibration of the building structure in the port with active damper systems. The immune system of organism in the real body regulates the antibody and T-cells to protect the attack from the foreign materials which are virus, germ cell, and other antigens. It has similar characteristics that are the adaptation and robustness to overcome disturbances and to control the plant of engineering application. At firstly, we build a model of the T-cell regulated immune response mechanism. We have also designed an I-PID controller focusing on the T-cell regulated immune response of biological immune system. Finally, we show that some computer simulations of the vibraton control for the building structure system with wind force excitation. These results for the proposed method also show that is has performance than other conventional controller design method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.1
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• pp.88-95
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• 2006

PID controllers, which have been widely used in industry, have a simple structure and robustness to modeling error. But They we difficult to have uniformly good control performance in system parameters variation or different velocity command. In this paper, we propose a nonlinear adaptive PID controller based on a cell-mediated immune response and a gradient descent learning. This algorithm has a simple structure and robustness to system parameters variation. To verify performances of the proposed nonlinear adaptive PID controller, the speed control of nonlinear DC motor is performed. The simulation results show that the proposed control systems are effective in tracking a command velocity under system parameters variation.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.5
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• pp.551-556
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• 2004

According to revealing the DNA sequence of human and living things, it increases that a demand on a new computational processing method which utilizes DNA sequence information. In this paper we propose a classification algorithm based on negative selection of the immune system to classify DNA patterns. Negative selection is the process to determine an antigenic receptor that recognize antigens, nonself cells. The immune cells use this antigen receptor to judge whether a self or not. If one composes n group of antigenic receptor for n different patterns, they can classify into n patterns. In this paper we propose a pattern classification algorithm based on negative selection in nucleotide base level and amino acid level.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.6
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• pp.699-704
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• 2004

This paper proposes a Distributed Autonomous Robotic System(DARS) based on an Artificial Immune System(AIS) and a Classifier System(CS). The behaviors of robots in the system are divided into global behaviors and local behaviors. The global behaviors are actions to search tasks in environment. These actions are composed of two types: aggregation and dispersion. AIS decides one among these two actions, which robot should select and act on in the global. The local behaviors are actions to execute searched tasks. The robots learn the cooperative actions in these behaviors by the CS in the local. The proposed system is more adaptive than the existing system at the viewpoint that the robots learn and adapt the changing of tasks.