• Proceedings of the KSME Conference
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• 2005.11a
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• pp.214.1-214.1
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• 2005

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.532-532
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• 2000

Conventional artificial intelligence systems are not properly responding under dynamically changing environments. To overcome this problem, reactive planning systems implementing new Al principles, called behavior-based Al or emergent computation, have been proposed and confirmed their usefulness. As another alternative, biological information processing systems may provide many feasible ideas to these problems. Immune system, among these systems, plays important roles to maintain its own system against dynamically changing environments. Therefore, immune system would provide a new paradigm suitable for dynamic problem dealing with unknown environments. In this paper, a new approach to behavior-based Al by paying attention to biological immune system is investigated. The feasibility of this method is confirmed by applying to behavior control of an autonomous mobile robot in cluttered environment.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.115.5-115
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• 2001

This paper suggests that the immune algorithm can effectively be used in tuning of a multivariable system. Then artificial immune network always has a new paraller decentralized processing mechanism for various situations, since antibodies communication to each other among different species of antibodies/B-cells through the simulation and suppression chains among antibodies that form a large-scaled network. In addition to that, the structure of the network is not fixed, but varies continuously. That is, the artificial immune network flexibly self-organizes according to dynamic changes of external environment (meta-dynamics function). However, up to the present time, models based on the conventional crisp approach ...

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.4
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• pp.51-58
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• 2004

This paper proposes a new artificial immune approach to on-line hardware test which is the most indispensable technique for fault tolerant hardware. A novel algorithm of generating tolerance conditions is suggested based on the principle of the antibody diversity. Tolerance conditions in artificial immune system correspond to the antibody in biological immune system. In addition, antigen presenting cell (APC) is realized by Quine-McCluskey method in this algorithm and tolerance conditions are generated through GA (Genetic Algorithm). The suggested method is applied to the on-line monitoring of a typical FSM (a decade counter) and its effectiveness is demonstrated by the computer simulation.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.03a
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• pp.373-379
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• 1999

This pqer investigates the subject of intrusion detection over networks. Existing network-based IDS's are categorised into three groups and the overall architecture of each group is summarised and assessed. A new methodology to this problem is then presented, which is inspired by the human immune system and based on a novel artificial immune model. The architecture of the model is presented and its characteristics are compared with the requirements of network-based IDS's. The paper concludes that this new approach shows considerable promise for future network-based IDS's.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1286-1290
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• 2004

This paper proposes a Distributed Autonomous Robotic System (DARS) based on an Artificial Immune Network (AIN) 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. AIN decides one between 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 relation between global and local increases the performance of system. Also, the proposed system is more adaptive than the existing system at the viewpoint that the robots learn and adapt the changing of tasks.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.12
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• pp.1079-1085
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• 2000

In this paper, we propose a method of cooperative control (T-cell modeling) and selection of group behavior strategy (B-cell modeling) based on immune system in distributed autonomous robotic system (DARS). An immune system is the living bodys self-protection and self-maintenance system. these features can be applied to decision making of the optimal swarm behavior in a dynamically changing environment. For applying immune system to DARS, a robot is regarded as a B-cell, each environmental condition as an antigen, a behavior strategy as an antibody, and control parameter as a T-cell, respectively. When the environmental condition (antigen) changes, a robot selects an appropriate behavior strategy (antibody). And its behavior strategy is stimulated and suppressed by other robots using communication (immune network). Finally, much stimulated strategy is adopted as a swarm behavior strategy. This control scheme is based on clonal selection and immune network hypothesis, and it is used for decision making of the optimal swarm strategy. Adaptation ability of the robot is enhanced by adding T-cell model as a control parameter in dynamic environments.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.35.4-35
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• 2002

$\textbullet$ Intrusion Detection Algorithm based on Artificial Immune System 1. Introduction 2. Research Background 3. The adaptation algorithm of SYN flooding attack 4. SIMULATION 5. Conclusion 6. References

• Proceedings of the Korea Database Society Conference
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• 1999.06a
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• pp.373-379
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• 1999

This paper investigates the subject of intrusion detection over networks. Existing network-based IDS's are categorised into three groups and the overall architecture of each group is summarised and assessed. A new methodology to this problem is then presented, which is inspired by the human immune system and based on a novel artificial immune model. The architecture of the model is presented and its characteristics are compared with the requirements of network-based IDS's. The paper concludes that this new approach shows considerable promise for future network-based IDS's

• Smart Structures and Systems
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• v.6 no.4
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• pp.389-403
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• 2010

By using image recognition technology, this paper presents a new fault diagnosis method for rotating machinery with artificial immune algorithm. This method focuses on the vibration state parameter image. The main contribution of this paper is as follows: firstly, 3-D spectrum is created with raw vibrating signals. Secondly, feature information in the state parameter image of rotating machinery is extracted by using Wavelet Packet transformation. Finally, artificial immune algorithm is adopted to diagnose rotating machinery fault. On the modeling of 600MW turbine experimental bench, rotor's normal rate, fault of unbalance, misalignment and bearing pedestal looseness are being examined. It's demonstrated from the diagnosis example of rotating machinery that the proposed method can improve the accuracy rate and diagnosis system robust quality effectively.