Results 241 to 250 of about 1,097,686 (283)

Negative Selection Algorithm-Based Motor Fault Diagnosis

The Sixth International Conference on Intelligent Systems and Knowledge Engineering (ISKE2011), Shanghai, China, Dec. 15-17, 2011, 2011
In this paper, a Negative Selection Algorithm (NSA)-based motor fault diagnosis scheme is proposed. The hierarchical fault diagnosis scheme takes advantage of the feature signals of the healthy motors so as to generate the NSA detectors, and uses the analysis of the activated detectors for fault diagnosis.
Xiao-Zhi Gao, Xiaolei Wang, Kai Zenger, Xiaofeng Wang   +3 more
openaire   +4 more sources

Negative Selection Algorithm Based Intrusion Detection Model

2020 IEEE 20th Mediterranean Electrotechnical Conference ( MELECON), 2020
The ever-growing security challenges have been a hindrance to the success of Information Technology Innovations due to multifaceted network intrusions. Hence, it becomes imperative to provide tools that can address without compromising integrity, confidentiality and availability of network resources.
Salau-Ibrahim Taofeekat Tosin, Jimoh Rasheed Gbenga   +1 more
openaire   +1 more source

Outliers detection based on negative selection algorithm

2010 International Conference on Communications, Circuits and Systems (ICCCAS), 2010
This paper presents a new approach to detect outliers. This paper detailedly introduces how to apply negative selection algorithm in outliers detection. Firstly, the maximum distance among all points is divided into a certain number of ranges which are encoded to binary codes.
null Zhang Xiaoling, null Wen Jun, null Wan XiaoFeng   +2 more
openaire   +1 more source

Negative selection algorithm based on immune suppression

2009 International Conference on Machine Learning and Cybernetics, 2009
The negative selection algorithm (NSA) is one of models in artificial immune systems. In this paper, two issues existed in traditional NSAs are described. Inspired by immune suppression mechanism, a novel framework of NSA that combining boundary selves and detectors to perform detection is proposed.
null Gui-Yang Li, Tao Li, null Jie Zeng, null Hai-Bo Li   +3 more
openaire   +1 more source

Quantum-Negative Selection Algorithm for Associative Classification

2012 IEEE International Conference on Granular Computing, 2012
Most of classification and rule learning algorithms in machine learning use heuristic search to find part of rules for classification. Classification Associative Classification (AC) has shown a great dominance over many classification techniques. It integrates the rule discovery and classification process to build the classifier that supports decision ...
Omar S. Soliman, Amr Adly
openaire   +1 more source

Motor fault diagnosis using negative selection algorithm

Neural Computing and Applications, 2013
In this paper, we propose a novel multi-level negative selection algorithm (NSA)-based motor fault diagnosis scheme. The hierarchical fault diagnosis approach takes advantage of the feature signals of the healthy motors so as to generate the NSA detectors and further uses the analysis of the activated detectors for fault diagnosis.
X. Z. Gao, X. Wang, K. Zenger
openaire   +1 more source

Intrusion detection oriented distributed negative selection algorithm

Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02., 2004
The negative selection algorithm proposed by Forrest et al. (1994) is a very significant change detection algorithm based on the generation process of T-Cells process in biological system. But when negative selection algorithm is used in distributed intrusion detection, the first problem that we meet is how to distribute the detectors in all detection ...
null Wenjian Luo, null Xianbin Cao, null Jiying Wang, null Xufa Wang   +3 more
openaire   +1 more source

A negative selection algorithm based on adaptive immunoregulation

2020 5th International Conference on Computational Intelligence and Applications (ICCIA), 2020
Negative selection algorithm (NSA) is an important detectors training algorithm in artificial immune system (AIS). In NSAs, the self radius and location of detectors affect the performance of algorithms. However, the traditional NSAs preset the self radius empirically and generate detectors randomly without considering the distribution of antigens ...
Hongli Deng, Tao Yang
openaire   +1 more source

A Negative Selection Algorithm-based motor fault detection scheme

2011 Seventh International Conference on Natural Computation, 2011
In this paper, we propose a Negative Selection Algorithm (NSA)-based motor fault detection system. Only the feature signals of the healthy motors are needed here for generating the NSA detectors. Different from the conventional fault detection approaches, no prior knowledge of the motor fault types is assumed to be known beforehand in the proposed ...
Gao, X.Z., Wang, X., Ovaska, S.J., Arkkio, A., Zenger, K.   +5 more
openaire   +3 more sources

Particle Swarm Optimization of detectors in Negative Selection Algorithm

2007 IEEE International Conference on Systems, Man and Cybernetics, 2007
This paper proposes a particle swarm optimization (PSO)-based detector optimization scheme in the negative selection algorithm (NSA). The NSA is a natural immune response inspired pattern discrimination method. In the new scheme, the NSA detectors are optimized by the PSO to collectively occupy the maximal coverage of the nonself space so that they can
X. Z. Gao, S. J. Ovaska, X. Wang
openaire   +1 more source