Multi-Search Strategy-based Improved Water Flow Optimizer Algorithm for Cluster Analysis by Prateek Thakral, Yugal Kumar

“…Heuristic algorithms are also proposed to alleviate the problems of traditional clustering algorithms. …”
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Pedestrian Re-Recognition Algorithm Based on Optimization Deep Learning-Sequence Memory Model by Feng-Ping An

“…It can help relay tracking and criminal suspect detection in large-scale video surveillance systems. …”
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Optical fiber eavesdropping detection method based on machine learning by Xiaolian CHEN, Yi QIN, Jie ZHANG, Yajie LI, Haokun SONG, Huibin ZHANG

“…Optical fiber eavesdropping is one of the major hidden dangers of power grid information security,but detection is difficult due to its high concealment.Aiming at the eavesdropping problems faced by communication networks,an optical fiber eavesdropping detection method based on machine learning was proposed.Firstly,seven-dimensions feature vector extraction method was designed based on the influence of eavesdropping on the physical layer of transmission.Then eavesdropping was simulated and experimental feature vectors were collected.Finally,two machine learning algorithms were used for classification detection and model optimization.Experiments show that the performance of the neural network classification is better than the K-nearest neighbor classification,and it can achieve 98.1% eavesdropping recognition rate in 10% splitting ratio eavesdropping.…”
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Object Detection Method of Inland Vessel Based on Improved YOLO by Yaoqi Wang, Jiasheng Song, Yichun Wang, Rongjie Wang, Hongyu Chen

“…In order to solve the problems of low accuracy of the current mainstream target detection algorithms in identifying small target ships, complex background interference such as coastline buildings and trees, and the influence of ship occlusion on ship target detection, an inland river ship detection method based on improved YOLOv10n: CDS-YOLO is proposed under the premise of keeping the model lightweight. …”
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A Special Points and Neural Network-Based Dynamic Multi-Objective Optimization Algorithm by Sanyi Li, Wenjie Hou, Peng Liu, Weichao Yue, Qian Wang

“…This paper introduces a special points and neural network- based dynamic multi-objective optimization algorithm (SPNN-DMOA) for solving dynamic multi-objective optimization problems (DMOPs) with an irregularly changing pareto set. …”
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Elevator Operation Health Diagnosis using Vibration Region Segmentation Algorithm via Internet by Lin Hsiung-Cheng, Peng Yan-Hao

“…For this reason, vibration analysis is considered an important topic for elevator maintenance as it can be used to detect potential problems before breakdown. Currently, vibration measurement is typically performed using vibration analyzers operated by personnel, resulting in a time-consuming process and experience-dependent interpretation. …”
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Early Fault-Tolerant Quantum Algorithms in Practice: Application to Ground-State Energy Estimation by Oriel Kiss, Utkarsh Azad, Borja Requena, Alessandro Roggero, David Wakeham, Juan Miguel Arrazola

“…We investigate the feasibility of early fault-tolerant quantum algorithms focusing on ground-state energy estimation problems. …”
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Constitutional-Legal Aspect of Creating Large Language Models: the Problem of Digital Inequality and Linguistic Discrimination by I. G. Ilin

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Detection Model for 5G Core PFCP DDoS Attacks Based on Sin-Cos-bIAVOA by Zheng Ma, Rui Zhang, Lang Gao

“…After rigorous testing across a spectrum of attack scenarios, the proposed detection model exhibits superior performance compared to traditional DDoS detection algorithms. …”
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An Improved Autonomous Emergency Braking Algorithm for AGVs: Enhancing Operational Smoothness Through Multi-Stage Deceleration by Wenbo Li, Junting Qiu

“…This paper proposes an improved Autonomous Emergency Braking (AEB) algorithm to tackle these problems. The algorithm employs a stepwise deceleration strategy, effectively reducing the frequency of sudden stops and enhancing the system’s operational smoothness. …”
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Research of Pedestrian Detection Methods with Anchor Frame Based on Deep Learning by Yan Tao

“…The occlusion problem and the scale change problem are one of the main causes of omission and false detection problems in practical applications of pedestrian detection. …”
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Fault detection and diagnosis method for heterogeneous wireless network based on GAN by Xiaorong ZHU, Peipei ZHANG

“…Aiming at the problem that in the process of network fault detection and diagnosis,how to train the precise fault diagnosis and detection model based on small data volume,a fault diagnosis and detection algorithm based on generative adversarial networks (GAN) for heterogeneous wireless networks was proposed.Firstly,the common network fault sources in heterogeneous wireless network environment was analyzed,and a large number of reliable data sets was obtained based on a small amount of network fault samples through GAN algorithm.Then,the extreme gradient boosting (XGBoost) algorithm was used to select the optimal feature combination of input parameters in the fault detection stage and completed fault diagnosis and detection based on these data.Simulation results show that the algorithm can achieve more accurate and efficient fault detection and diagnosis for heterogeneous wireless networks,with an accuracy of 98.18%.…”
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Fault detection and diagnosis method for heterogeneous wireless network based on GAN by Xiaorong ZHU, Peipei ZHANG

“…Aiming at the problem that in the process of network fault detection and diagnosis,how to train the precise fault diagnosis and detection model based on small data volume,a fault diagnosis and detection algorithm based on generative adversarial networks (GAN) for heterogeneous wireless networks was proposed.Firstly,the common network fault sources in heterogeneous wireless network environment was analyzed,and a large number of reliable data sets was obtained based on a small amount of network fault samples through GAN algorithm.Then,the extreme gradient boosting (XGBoost) algorithm was used to select the optimal feature combination of input parameters in the fault detection stage and completed fault diagnosis and detection based on these data.Simulation results show that the algorithm can achieve more accurate and efficient fault detection and diagnosis for heterogeneous wireless networks,with an accuracy of 98.18%.…”
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Statistically Bounding Detection Latency in Low-Duty-Cycled Sensor Networks by Yanmin Zhu

“…This paper studies the fundamental problem of bounding detection delays when the sensor network is low duty cycled. …”
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Social Network Analysis: A Novel Paradigm for Improving Community Detection by Rodrigo Hernández, Inmaculada Gutiérrez, Javier Castro

“…One of the fundamental challenges in this field is the community detection problem, which involves identifying groups within networks. …”
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Analysis of Asymmetric Piecewise Linear Stochastic Resonance Signal Processing Model Based on Genetic Algorithm by Lina He, Chuan Jiang

“…Because the existing stochastic resonance system model has the problem of poor performance, an asymmetric piecewise linear stochastic resonance system model is proposed, and the parameters of the model are optimized by a genetic algorithm. …”
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Covariance Blind Detection Method Based on Eigenvector in Cognitive Radio Network by Yingxue Li, Jing Lei, Shiyuan Zhong, Chunming Huang, Chao Huang

“…As the blind detection algorithm has the shortcoming that they need information about the channel and more than two cognitive users to detect the primary user,a new blind detection algorithm based on eigenvector using the difference of correlation between the primary user signal and noise signal covariance matrix was presented,and a closed expression was derived for the probability of false alarm and threshold.The proposed method overcomes the noise uncertainty problem only with two cognitive relays and performs well without information about the channel,primary user and noise.Numerical simulations show that the new detector performs better than other detectors.…”
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Covariance Blind Detection Method Based on Eigenvector in Cognitive Radio Network by Yingxue Li, Jing Lei, Shiyuan Zhong, Chunming Huang, Chao Huang

“…As the blind detection algorithm has the shortcoming that they need information about the channel and more than two cognitive users to detect the primary user,a new blind detection algorithm based on eigenvector using the difference of correlation between the primary user signal and noise signal covariance matrix was presented,and a closed expression was derived for the probability of false alarm and threshold.The proposed method overcomes the noise uncertainty problem only with two cognitive relays and performs well without information about the channel,primary user and noise.Numerical simulations show that the new detector performs better than other detectors.…”
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Using fuzzy clustering to reconstruct alert correlation graph of intrusion detection by MA Lin-ru1, YANG Lin2, WANG Jian-xin2, TANG Xin2

“…In order to solve the problem, an algorithm was proposed to reconstruct attack scenario using fuzzy clustering. …”
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Multiobjective Optimization-Based Hyperspectral Unsupervised Band Selection for Anomaly Detection by Shihui Liu, Bing Xue, Meiping Song, Haimo Bao, Mengjie Zhang

“…Specifically, for the first problem, by calculating the degree of deviation of the band, the noise estimates of the band, and the degree of redundancy between bands, an unsupervised BS algorithm for anomaly detection tasks, based on MO, is designed. …”
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