Negative Selection Algorithm for Unsupervised Anomaly Detection by Michał Bereta

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Fault Detection of Aircraft Control System Based on Negative Selection Algorithm by Jie Chen, Senyao Chen, Cunbao Ma, Zhengdong Jing, Qingshan Xu

“…In this paper, by taking advantage of the strong leaning and intelligent recognition ability and the characteristic of less information required in the negative selection artificial immune system, a fault detection method is proposed for aircraft control system based on negative selection algorithm. …”
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Developing an Immune Negative Selection Algorithm for Intrusion Detection in NSL-KDD data Set by Baghdad Science Journal

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Detecting Positive and Negative Changes From SAR Images by an Evolutionary Multi-Objective Approach by Shuang Liang, Hao Li, Yun Zhu, Maoguo Gong

“…Therefore, the changed areas can be further classified into positive and negative changed classes. This paper presents an unsupervised change detection approach for detecting the positive and negative changes based on a multi-objective evolutionary algorithm. …”
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Application of Immune Complement Algorithm to NSL-KDD Intrusion Detection Dataset by Mafaz Khalil Alanezi, Najlaa Aldabagh

“…</span> <span>This Paper presents a description of an intrusion detection approach modeled on the basis of three bio-inspired concepts namely, Negative selection, Positive selection and complement system. …”
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Integrated artificial immune system for intrusion detection by Yue-bing CHEN, Chao FENG, Quan ZHANG, Chao-jing TANG

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Recursive Sentiment Detection Algorithm for Russian Sentences by Anatoliy Y. Poletaev, Ilya V. Paramonov

“…The article introduces a rule-based sentiment detection algorithm for Russian sentences. The algorithm is based on the assumption that the sentiment of a phrase can be determined by the sentiments of its parts by the recursive application of appropriate semantic rules to the sentiments of its parts organized as a constituency parse tree. …”
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Binocular Vision-Based Target Detection Algorithm by Huiguo Zhang

“…In the field of target detection, algorithms are challenged with multi-objective optimization problems in identifying detection targets, and it is also crucial to improve the recognition of small and insignificant targets. …”
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Semi-supervised dynamic community detection based on non-negative matrix factorization by Zhen-chao CHANG, Hong-chang CHEN, Rui-yang HUANG, Hong-tao YU, Yang LIU

“…How to effectively combine the network structures on different time points was the key and difficulty to affect the performance of detection algorithms. Based on this, a semi-supervised dynamic community algorithm SDCD based on non-negative matrix factorization, which effectively extracted the historical stability structure unit firstly, and then use it as a regularization item supervision of nonnegative matrix decomposition, to guide the network community detection on current moment. …”
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Network intrusion detection based on improved KNN algorithm by Hongsheng Bao, Jie Gao

“…An initial K-nearest neighbor algorithm based on representative points is proposed. …”
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Feature-based enhanced boosting algorithm for depression detection by Muhammad Sadiq Rohei, Kasturi Dewi Varathan, Shivakumara Palaiahnakote, Nor Badrul Anuar

“…Fortunately, machine learning and deep learning techniques have demonstrated excellent results in the early detection of depression using social media data. Most recently, researchers have utilized boosting algorithms including pre-defined boosting algorithms or built their own boosting algorithm for the detection of depression. …”
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Fake News Detection Model Basing on Machine Learning Algorithms by Mohammed A. Taha, Haider D. A. Jabar, Widad K. Mohammed

“…Malicious misinformation on social media negatively affects societies, especially during crises like terrorist attacks, riots, and natural disasters. …”
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An Intrusion Detection Approach based on the Combination of Oversampling and Undersampling Algorithms by Ahmet Okan Arık, Gülsüm Çiğdem Çavdaroğlu

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Application of Artificial Intelligence for the Implementation of Mismatch Negativity Potential Algorithms in Industrial Automated Predictive Maintenance Systems by Alexander Yu. Chesalov

“…The basic architecture of the automated system is proposed, which takes into account the need to use software algorithms of mismatch negativity potential. It consists of modules of data verification, model training, anomaly detection, predictive model, visualization and module of integration with other industrial information and automated systems. …”
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Enhancing Drone Detection via Transformer Neural Network and Positive–Negative Momentum Optimizers by Pavel Lyakhov, Denis Butusov, Vadim Pismennyy, Ruslan Abdulkadirov, Nikolay Nagornov, Valerii Ostrovskii, Diana Kalita

“…In this paper, we propose a Yolov12 architecture with positive–negative pulse-based optimization algorithms to solve the problem of drone detection on video data. …”
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Research on Asphalt Pavement Surface Distress Detection Technology Coupling Deep Learning and Object Detection Algorithms by Hong Zhang, Yuanshuai Dong, Yun Hou, Xiangjun Cheng, Peiwen Xie, Keming Di

“…Additionally, the YOLOv5 object detection algorithm, combined with convolutional deep learning techniques, was employed to classify and identify pavement surface distresses in the collected images. …”
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Multiobject Detection Algorithm Based on Adaptive Default Box Mechanism by Jinling Li, Qingshan Hou, Jinsheng Xing

“…Experimental results show that, compared with the traditional SSD algorithm, the improved algorithm has a better detection effect and higher accuracy in complex scenes.…”
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Malicious Domain Names Detection Algorithm Based on N-Gram by Hong Zhao, Zhaobin Chang, Guangbin Bao, Xiangyan Zeng

“…In the experiments on Alexa 2017 and Malware domain list, the proposed detection algorithm yielded an accuracy rate of 94.04%, a false negative rate of 7.42%, and a false positive rate of 6.14%. …”
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Development of deep learning algorithm for detecting dyskalemia based on electrocardiogram by Jung Nam An, Minje Park, Sunghoon Joo, Mineok Chang, Do Hyoung Kim, Dong Geum Shin, Yeongyeon Na, Jwa-Kyung Kim, Hyung-Seok Lee, Young Rim Song, Yeha Lee, Sung Gyun Kim

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An Improved Small Target Detection Algorithm Based on YOLOv8s by G. Ma, C. Xu, Z. Xu, X. Song

“…Due to challenges such as the small size of targets, complex backgrounds, limited feature extraction capa-bilities, and frequent false positives and false negatives, traditional detection algorithms often perform poorly in small object detection tasks. …”
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