• 산업공학
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• 제20권4호
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• pp.458-468
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• 2007

Artificial immune systems (AIS) are one of natural computing inspired by the natural immune system. The fault detection, the pattern recognition, the system control and the optimization are major application area of artificial immune systems. This paper gives a concept of artificial immune systems and useful techniques as like the clonal selection, the immune network theory and the negative selection. A concise survey on the optimization problem based on artificial immune systems is generated. The overall performance of artificial immune systems for the optimization problem is discussed.

• 대한전기학회논문지:시스템및제어부문D
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• 제50권11호
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• pp.522-531
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• 2001

Recently conventional artificial intelligence(AI) approaches have been employed to build action selectors for the autonomous mobile robot(AMR). However, in these approaches, the decision making process to choose an action from multiple competence modules is still an open question. Many researches have been focused on the reactive planning systems such as the biological immune system. In this paper, we attempt to construct an action selector for an AMR based on the artificial immune network and internet. The information from vision sensors is used for antibody. We propose a learning method for artificial immune network using evolutionary algorithm to produce antibody automatically. The internet environment for an AMR action selector shows the usefulness of the proposed learning artificial immune network application.

• 대한전기학회논문지:시스템및제어부문D
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• 제52권8호
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• pp.471-481
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• 2003

The acts of biological immune system are similar to the navigation for autonomous mobile robots under dynamically changing environments. In recent years, many researchers have studied navigation algorithms using artificial immune networks. Conventional artificial immune algorithms consist of an obstacle-avoidance behavior and a goal-reaching behavior. To select a proper action, the navigation algorithm should combine the obstacle-avoidance behavior with the goal-reaching behavior. In this paper, the neural network is employed to combine the behaviors. The neural network is trained with the surrounding information. the outputs of the neural network are proper combinational weights of the behaviors in real-time. Also, a velocity control algorithm is constructed with the artificial immune network. Through a simulation study and experimental results for a autonomous mobile robot, we have shown the validity of the proposed navigation algorithm.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.220-223
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• 2003

In this paper, we optimize distributed autonomous robotic system based on artificial immune system. Immune system has B-cell and T-cell that are two major types of lymphocytes. B-cells take part in humoral responses that secrete antibodies and T-cells take part in cellular responses that stimulate or suppress cells connected to the immune system. They have communicating network equation, which have many parameters. The distributed autonomous robotics system based on this artificial immune system is modeled on the B-cells and T-cells system. So performance of system is influenced by parameters of immune network equation. We can improve performance of Distributed autonomous robotics system based on artificial immune system.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 V
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• pp.2673-2676
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• 2003

This Paper proposes a new artificial immune approach to hardware test. 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. 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.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제3권1호
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• pp.23-26
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• 2003

This paper proposes a new artificial immune approach to hardware test. 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. 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.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2008년도 추계학술대회 및 정기총회
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• pp.236-246
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• 2008

We consider the Inventory Routing problem(IRP) for the vending machine operating system. An artificial immune system(AIS) is introduced to solve the IRP. The IPR is an rolling wave planning. The previous solution of IRP is one of good initial solution of current IRP. We introduce an Artificial Immune system with memory cell (AISM) which store previous solution in memory cell and use an initial solution for current problem. Experiment results shows that AISM reduced calculations time in relatively less demand uncertainty.

• Journal of Electrical Engineering and Technology
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• 제8권5호
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• pp.959-968
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• 2013

This paper presents a new approach with artificial immune system algorithm to solve the profit based unit commitment problem. The objective of this work is to find the optimal generation scheduling and to maximize the profit of generation companies (Gencos) when subjected to various constraints such as power balance, spinning reserve, minimum up/down time and ramp rate limits. The proposed hybrid method is developed through adaptive search which is inspired from artificial immune system and genetic algorithm to carry out profit maximization of generation companies. The effectiveness of the proposed approach has been tested for different Gencos consists of 3, 10 and 36 generating units and the results are compared with the existing methods.

• Smart Structures and Systems
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• 제6권4호
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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.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2000년도 추계학술발표논문집 (상)
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• pp.273-276
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• 2000

This paper describes on-going research, applying an artificial immune system to the problem of network intrusion detection. The paper starts by introducing the motivation and rationale of this research. After describing the overall architecture of the proposed artificial immune system fur network intrusion detection, the real network traffic data and its profile features used in this research are explained. As the first step of this effort, the negative selection algorithm, which is one of three significant evolutionary stages comprising an overall artificial immune system, is investigated and initial results are briefly discussed. Finally, the direction of future work is discussed based on this initial result and the contribution of this research is addressed.