A real-valued negative selection algorithm with good mathematical foundation is presented to solve some of the drawbacks of previous approach. Specifically, it can produce a good estimate of the optimal number of dete...
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A real-valued negative selection algorithm with good mathematical foundation is presented to solve some of the drawbacks of previous approach. Specifically, it can produce a good estimate of the optimal number of detectors needed to cover the non-self space, and the maximization of the non-self coverage is done through an optimization algorithm with proven convergence properties. Experiments are performed to validate the assumptions made while designing the algorithm and to evaluate its performance.
The V-detector algorithm is a real-valued negative selection algorithm with variable-sized detectors. In this paper, several flaws existed in the algorithm are investigated and analyzed. An improved V-detector algorit...
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ISBN:
(纸本)9781424447053
The V-detector algorithm is a real-valued negative selection algorithm with variable-sized detectors. In this paper, several flaws existed in the algorithm are investigated and analyzed. An improved V-detector algorithm is also proposed and implemented. The improved algorithm divides the collection of self samples into boundary selves and non-boundary selves. The identifying and recording mechanism of boundary self are introduced during the generation of detectors. The experiment results showed that the new algorithm covers the holes existed in boundary between self region and non-self region more effectively than traditional negative selection algorithm does. In the meantime, the new algorithm can reduce the number of detectors under the circumstance of ensuring detection performance.
Artificial immune system (AIS) mimicks the superior properties of biological immune system and provides an effective method in intelligent computing and intelligent system designing. But the disease-causing mechanisms...
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ISBN:
(纸本)9781424427239
Artificial immune system (AIS) mimicks the superior properties of biological immune system and provides an effective method in intelligent computing and intelligent system designing. But the disease-causing mechanisms of immune pathology have led to sever security problems in artificial immune system. In the paper, we analyzed the basic principles of immune protection and immune pathology of biological system considering its application in artificial immune system. Then we take artificial immune defending system as an example to analyze the cause and potential influence of immune pathology on AIS. As to the different security problems from immunodeficiency, hypersensitivity and autoimmunity, we put forward corresponding measures to reinforce the security, robustness and stability of artificial immune system and thus effectively avoid these problems.
There are many uncertain stochastic factors in the process of the airdrome flight delay forecast, especially the cumulate diversification and propagation effect of the flight delays. The paper is on the base of the im...
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ISBN:
(纸本)9780769537450
There are many uncertain stochastic factors in the process of the airdrome flight delay forecast, especially the cumulate diversification and propagation effect of the flight delays. The paper is on the base of the immune detection for the airdrome flight delay status, considering the dynamic diversification and stochastic factors of the airdrome flight delays. Propose the dynamic immune forecasting method of the airdrome flight delays under the stochastic factors and establish corresponding collection of self, detecting cells, the information of antigens and the matching model between them through setting up correspondence between the biological immune mechanism and flight operating mechanism. The result shows the method can forecast the count of flight delay in the next period of time accurately and has a good real-time characteristic.
Fault diagnosis has been recognized as one of the key issues in wireless sensor networks. Considering distribution feature of sensor node, however, the fault happened in wireless sensor networks is usually random and ...
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ISBN:
(纸本)9780819478047
Fault diagnosis has been recognized as one of the key issues in wireless sensor networks. Considering distribution feature of sensor node, however, the fault happened in wireless sensor networks is usually random and unpredictable. The conventional diagnosis approaches become increasingly difficult to deal with. As a result, the application is limited seriously. To solve the problem, a new approach based on artificial immune system for fault diagnosis is proposed. The normal and abnormal character patterns generated by a network simulator for wireless sensor networks, respectively, are regarded as the self and antigen of artificial immune system. According to a real-valued negative selection algorithm, the detectors are generated to improve the covering ability of non- self space. Taking detector as antibody, an immunity calculation is executed by the distribution zones of antibody and evolution learning mechanism of artificial immune system. The type of antigen is decided based on the clustering distribution of cloned and matured antibody. The example shows that the approach has better accuracy and the capability of self-adaptive for the fault diagnosis in wireless sensor networks.
The V-detector generation algorithm is a kind of negative selection algorithm (NSA) inspired by biological immune system (BIS). In this paper, V-detector generation algorithm is simply introduced. The problem that V-d...
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ISBN:
(纸本)9780769536996
The V-detector generation algorithm is a kind of negative selection algorithm (NSA) inspired by biological immune system (BIS). In this paper, V-detector generation algorithm is simply introduced. The problem that V-detector generation algorithm call not meet the change of parameters in significant level is also pointed out. This problem will cause instable algorithm performance. In the meantime, it will cause the algorithm failed under the circumstance of some parameter values. This paper analyzed the reason Him caused file problem theoretically and file relevant solution is proposed. The experiment results showed that file proposed solution solved the problem existed in original algorithm successfully and make the performance more stable and reliable. The improved algorithm can really adapt to different values of significant level and obtain better detection performance.
Fault diagnosis is important to ensure the continuity in the systems that the studies in this area have increased. The effectiveness of fault diagnosis methods has been enhanced by using intelligent computing techniqu...
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Fault diagnosis is important to ensure the continuity in the systems that the studies in this area have increased. The effectiveness of fault diagnosis methods has been enhanced by using intelligent computing techniques. In this study, a fault diagnosis method based on fuzzy logic and negativeselection is proposed. In the proposed algorithm, the broken rotor bar related features are extracted using negative selection algorithm that is a component of the artificial immune system. In addition, the direction of spectrum changing obtained using the motor current signature analysis is given to fuzzy logic system and the faults are diagnosed. A new weighted affinity measurement is presented for negativeselection. The broken rotor bar faults, stator and bearing friction faults occurred in induction motors can be diagnosed by using proposed method. The output of the method gives both the fault type and the severity of fault to determine the multiple faults. The performance of proposed method is verified using healthy and faulty motor data that are obtained as simulation and experimentally.
The detector generation algorithm is the core of a negative selection algorithm (NSA). In most previous work, the NSAs generate the detector set randomly, which cannot guarantee to obtain an efficient detector set. To...
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ISBN:
(纸本)9780769539294
The detector generation algorithm is the core of a negative selection algorithm (NSA). In most previous work, the NSAs generate the detector set randomly, which cannot guarantee to obtain an efficient detector set. To generate an approximately optimal detector set, in this paper, a novel detector generation algorithm for the Real-Valued negative selection algorithm (RNSA) is proposed. The proposed algorithm, named as the EvoSeedRNSA, adopts a genetic algorithm to evolve the random seeds to obtain an optimized detector set. The experimental results demonstrate that the EvoSeedRNSA has a better performance.
There are many uncertain stochastic factors in the process of the airdrome flight delay forecast, especially the cumulate diversification and propagation effect of the flight delays. The paper is on the base of the im...
详细信息
There are many uncertain stochastic factors in the process of the airdrome flight delay forecast, especially the cumulate diversification and propagation effect of the flight delays. The paper is on the base of the immune detection for the airdrome flight delay status, considering the dynamic diversification and stochastic factors of the airdrome flight delays. Propose the dynamic immune forecasting method of the airdrome flight delays under the stochastic factors and establish corresponding collection of self, detecting cells, the information of antigens and the matching model between them through setting up correspondence between the biological immune mechanism and flight operating mechanism. The result shows the method can forecast the count of flight delay in the next period of time accurately and has a good real-time characteristic.
The V-detector generation algorithm is a kind of negative selection algorithm (NSA) inspired by biological immune system (BIS). In this paper, V-detector generation algorithm is simply introduced. The problem that V-d...
详细信息
The V-detector generation algorithm is a kind of negative selection algorithm (NSA) inspired by biological immune system (BIS). In this paper, V-detector generation algorithm is simply introduced. The problem that V-detector generation algorithm can not meet the change of parameters in significant level is also pointed out. This problem will cause instable algorithm performance. In the meantime, it will cause the algorithm failed under the circumstance of some parameter values. This paper analyzed the reason that caused the problem theoretically and the relevant solution is proposed. The experiment results showed that the proposed solution solved the problem existed in original algorithm successfully and make the performance more stable and reliable. The improved algorithm can really adapt to different values of significant level and obtain better detection performance.
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