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2011 International Conference on Power Electronics and Engineering Application

作者： Xu Aiqiang Liu Yong Zhao Xiuli Yang Chunying Li Tingjun Naval Aeronautical and Astronautical University

Concerned with the problem of lacking fault samples of complex equipments, it studies the principle and application of negative selection algorithm of artificial immune system. The detectors generation mechanism of real-valued negative selection algorithm is introduced. Intuitively, to maximize the covering produced by a set of detectors, it is necessary to reduce their overlapping and not covering the self set. This paper presents an optimization strategy base on re-heating simulated annealing algorithm to modify the position of detectors, not changing their number. This method can improve the covering effect of non-self space. The triangle training data are used to demonstrate the properties of optimized VRNS. Detection rate is improved and false alarming rate is decreased. It is used for fault detection in analog circuit;result demonstrates that the proposed algorithm is better than artificial neural network in fault detection of this circuit.

关键词： negative selection algorithm re-heating simulated annealing optimization fault detection

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An Improved Detector Set Generation Mechanism in negative selection algorithm

An Improved Detector Set Generation Mechanism in Negative Se...

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2016 3rd International Conference on Information and Communication Technology for Education(ICTE 2016)

作者： Bo Hu Science and Technology College Jiangxi Normal University

in view of the shortcomings of the detector generation mechanism in the existing negative selection algorithm,a new method of boundary detection is proposed to deal with the problem of the boundary *** the algorithm,it is used as the self region of the body and its adjacent *** realization process and advantages of the algorithm are *** algorithm is validated by the synthetic data set 2 DSynthetic Data and the actual Iris data set and the Biomedical data *** results show that the detection rate of this algorithm is high,especially the points that are in the self and non self boundary can be detected effectively.

关键词： negative selection algorithm Boundary detection Detector Detection rate

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Integrated negative selection algorithm and Positive selection algorithm for Malware Detection

Integrated Negative Selection Algorithm and Positive Selecti...

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2016 IEEE International Conference on Progress in Informatics and Computing

作者： Fuyong Zhang Ying Ma School of Computer Science and Network Security Dongguan University of Technology School of Computer and Information Engineering Xiamen University of Technology

Run-time malware detection strategies are efficient and robust, which get more and more attention. In this paper, we use I/O Request Package（IRP） sequences for malware detection. N-gram will be used to analyze IRP sequences for feature extraction. Integrated negative selection algorithm（NSA） and Positive selection algorithm（PSA）, through a selection of ngram sequences which only exist in malware IRP sequences, we have more than 96% true positive rate and 0% false positive rate.

关键词： I/O Request Package artificial immune system negative selection algorithm positive selection algorithm malware detection

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A New negative selection algorithm and its Application in the Fault Diagnosis of the Pump-jack

A New Negative Selection Algorithm and its Application in th...

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7th World Congress on Intelligent Control and Automation (WCICA 2008), vol.5

作者： Weijian Ren Qiong Wang Daqing Petroleum Institute Daqing Heilongjiang China

The fault diagnosis of the pump-jack is as the background in the paper. A new negative selection algorithm is proposed combining the advantage of genetic algorithm and simulating annealing algorithm. The initial values of the detectors are initialized by genetic algorithm, thus the diversity of the detectors is retained, the scope of detecting is enlarged. The variable radius of detectors is introduced to cover non-self space efficiently. The redundancy of detectors is reduced and the efficiency is improved by using simulating annealing. The method is used to diagnosis the faults of the pump-jack. The results are better. Especially the method can diagnosis unknown faults. It has great potentiality.

关键词： negative selection algorithm Fault diagnosis Simulating annealing algorithm Variable radius

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Damage detection in composite beams using negative selection algorithm method

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Materials Today: Proceedings 2023年

作者： Kosanam Ashwini Sasmita Sahu Hemalata Jena Rita Kumari Sahu KIIT University Bhubaneswar 751024 India

Most of the structural members act under periodic loading conditions which lead to cracks or damages. The initiation of cracks may change the physical properties of a structure mostly the flexibility and stiffness changes. The dynamic changes will directly change the natural frequencies and mode shapes. This study was an adaptive evolutionary algorithm to identify the damage location based on the immune system of the vertebrates. The first three natural frequencies from FEA and experimental techniques act as an input to the negative selection algorithm. The proposed method results are compared with the results of experimental analysis and FEA. The percentage error in both cases was found to be 3 % which is measurable.

关键词： Damage Vibration Artificial immune system negative selection algorithm

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EvoSeedRNSAII: An improved evolutionary algorithm for generating detectors in the real-valued negative selection algorithms

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APPLIED SOFT COMPUTING 2014年 19卷 18-30页

作者： Zhang, Jie Luo, Wenjian Univ Sci & Technol China Sch Comp Sci & Technol Hefei 230027 Anhui Peoples R China Univ Sci & Technol China Anhui Key Lab Software Engn Comp & Commun Hefei 230027 Anhui Peoples R China

In the previous work, a detector generation algorithm, named as the EvoSeedRNSA, is proposed. A genetic algorithm is adopted in the EvoSeedRNSA to evolve the random seeds to generate an approximately optimal detector set. This paper proposes an improved EvoSeedRNSA, named as the EvoSeedRNSAII, to generate a more efficient detector set. A multi-group random seed encoding scheme is designed to represent the individuals and different detector generation sequences are discussed. The experiments demonstrate that the EvoSeedRNSAII has a better performance than the EvoSeedRNSA. (C) 2014 Elsevier B.V. All rights reserved.

关键词： negative selection algorithm Evolutionary algorithm Detector generation algorithm EvoSeedRNSA Encoding schemes

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An integrated approach to detect online financial transaction fraud using negative and clonal selection algorithms with AIS 3

An integrated approach to detect online financial transactio...

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3rd International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, IITCEE 2025

作者： Gupta, Rohan Ghanghas, Peshal Uie Chandigarh University Dept. of Ece Mohali India

ISBN: (纸本)9798331515911

The relevancy of fraud detection in account takeover fraud in online financial transactions is at it's peak. The traditional fraud detection approaches have seen a downwards trend. This paper adds more onto the utilization of Biological Immune System to level an AI-based Immune system for detecting frauds and the emerging patterns within it's domain. By implementing various machine learning algorithms such as negative and clonal selection the proposed system can accurately identify previously unknown fraud patterns and various attack strategies used by the unauthorized users and hackers. The integration of this approach seems promising in improving the security and enhancing the dependability of the transactions, hence, safeguarding people from account takeover fraud. © 2025 IEEE.

关键词： Artificial Immune system(AIS) Biological Immune System principles(BISP) clonal selection algorithm Fraud Detection (FD) negative selection algorithm online financial transaction fraud

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Artificial immunity-based energy theft detection for advanced metering infrastructures

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INTERNATIONAL JOURNAL OF CRITICAL INFRASTRUCTURE PROTECTION 2025年 48卷

作者： Fu, Jie Yang, Chengxi Liu, Yuxuan Zhang, Kunsan Li, Jiaqi Li, Beibei State Grid Fujian Elect Power Co Ltd Fuzhou 350003 Fujian Peoples R China Sichuan Univ Sch Cyber Sci & Engn Chengdu 610207 Sichuan Peoples R China

Advanced Metering Infrastructure (AMI) is envisioned to enable smart energy management and consumption while ensuring the integrity of real energy consumption data. However, existing smart meters, gateways, and communication channels are usually weakly protected, often opening a huge door for data eavesdroppers who may be easily to further construct energy thefts. Although some energy theft detection schemes have already been reported in the literature, they often fail to take into account the dense data distribution characteristics of energy consumption data, resulting in compromised detection performance. To this end, we in this paper propose a novel arTificial IM mune based E nergy theft D etection (TIMED) scheme, which can effectively identify five types of energy thefts. Specifically, we first develop an energy consumption data pre-processing method, which can effectively reduce the dimensionality of raw energy consumption data to facilitate the data analyzing efficiency. Second, we design a center-distance-based energy theft detector generation method to create high- quality detectors with low elimination rates. Last, we devise a nonself-based hole repair method for energy theft detectors, which can further reduce the false negative alarms. Extensive experiments on areal public AMI dataset demonstrate that the proposed TIMED scheme is highly effective in identifying pulse attacks, scaling attacks, ramping attacks, random attacks, and smooth-curve attacks. The results show that TIMED outperforms many existing machine learning and traditional artificial immunity-based energy theft detection methods.

关键词： Advanced metering infrastructure (AMI) Energy theft detection Artificial immunity negative selection algorithm

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An intelligent manufacturing system based on a recursive control structure

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FRONTIERS IN MECHANICAL ENGINEERING-SWITZERLAND 2025年 10卷

作者： Teng, Bingyan Nanjing Vocat Univ Ind Technol Sch Business & Trade Nanjing Peoples R China

Introduction The excessive uncertainty of in modern manufacturing systems is caused by machine failures, changes in material information, and other factors. In addition, the organizational production mode conflicts brought about by economic and technological development further exacerbate the perception of workshop interference in manufacturing *** In order to further improve the adaptability of manufacturing systems, a control technique based on recursive control structure is proposed, which introduces an immune working mechanism to design the framework network of multi-agent manufacturing systems. Meanwhile, a negative selection algorithm is used to construct an antibody training system that considers perturbation *** The results indicate that immune sensing nodes can effectively monitor manufacturing systems, reducing false alarm rates by over 4%. In the scheduling experiment, the completion time and equipment load improvement rate demonstrated by the research model were 3.29% and 12.38%, respectively. The production balance optimization rate exceeded 90%, far exceeding the results of traditional scheduling schemes, greatly improving the adaptive control capability of manufacturing system *** The regulatory approach proposed in this study can provide reference and assistance for improving the level of industrial production intelligence and establishing a sustainable economic system. However, the research results have not been applied to actual production processes, and the autonomy and coordination of intelligent manufacturing units in actual production processes still need to be further improved. In the future, research models and algorithms will be further explored in this area.

关键词： manufacturing systems recursive structure intelligent agents immune mechanism negative selection algorithm

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Using a Novel negative selection Inspired Anomaly Detection algorithm to Identify Corrupted Ribo-seq and RNA-seq Samples 19

Using a Novel Negative Selection Inspired Anomaly Detection ...

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10th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics (ACM-BCB)

作者： Perkins, Patrick Heber, Steffen North Carolina State Univ Bioinformat Res Ctr Raleigh NC 27695 USA North Carolina State Univ Dept Comp Sci Raleigh NC 27695 USA

ISBN: (纸本)9781450366663

RNA-seq and Ribo-seq are popular techniques for quantifying cellular transcription and translation. These experiments use next-generation sequencing to produce genome-wide high-resolution snapshots of the total populations of mRNAs and translating ribosomes within the investigated samples. When performed in concert, these experiments yield valuable information about protein synthesis rates and translational efficiency. Due to their intricate experimental protocols and demanding data processing requirements, quality control and analysis of such experiments are often challenging. Therefore, methods for accurately assessing data quality, and for identifying contaminated samples, are greatly needed. In the following we use a novel negative selection inspired algorithm called Boundary Detection Using Nearest Neighbors (BDUNN), for the identification of corrupted samples. Our algorithm constructs a detector set and reduced training set that defines the boundaries between normal data points and potential anomalies. Subsequently, a nearest neighbor algorithm is used to classify unseen observations. We compare the performance of BDUNN with other popular negative selection and one-class classification algorithms, and show that BDUNN is capable of accurately and efficiently detecting anomalies in standard anomaly detection datasets and simulated RNA-seq and Ribo-seq data sets. Furthermore, we have implemented our method within an existing R Shiny platform for analyzing RNA-seq an Ribo-seq datasets, which permits downstream analysis of anomalous samples.

关键词： Ribosome profiling RNA-seq anomaly detection sample quality machine learning negative selection algorithm

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