Bearing fault diagnosis method based on improved compressed sensing and deep multi-kernel extreme learning machine by FU Qiang, HU Dong, YANG Tongliang, LUO Guoqing, TAN Weimin

“…Secongly, the compressed data was used as the input signal for the D-MKELM. Particle swarm optimization (PSO) algorithm was applied to optimize critical parameters, enabling intelligent fault diagnosis. …”
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Enhancing IoT cybersecurity through lean-based hybrid feature selection and ensemble learning: A visual analytics approach to intrusion detection. by Islam Zada, Esraa Omran, Salman Jan, Hessa Alfraihi, Seetah Alsalamah, Abdullah Alshahrani, Shaukat Hayat, Nguyen Phi

“…In this paper, a Lean-based hybrid Intrusion Detection framework using Particle Swarm Optimization and Genetic Algorithm (PSO-GA) to select the features and Extreme Learning Machine and Bootstrap Aggregation (ELM-BA) to classify the features is introduced. …”
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Development of a standardized data collection and intelligent fabric quality prediction system for the weaving department by Ning Dai, Lunjun Li, Kaixin Xu, Zhehao Lu, Xudong Hu, Yanhong Yuan

“…This study leverages the standardization and interoperability features of open platform communications unified architecture technology to facilitate data acquisition within the weaving department, establishing a reliable Internet of Things framework that supports subsequent fabric quality prediction, and optimizing the back propagation neural network through the K-means clustering algorithm and particle swarm optimization to predict the type and number of fabric defects. …”
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Estimation of Elasticity of Porous Rock Based on Mineral Composition and Microstructure by Zaobao Liu, Jianfu Shao, Weiya Xu, Chong Shi

“…Then the support vector machine (SVM) optimized by the particle swarm optimization algorithm (PSO) is examined to generate estimations of the ECS based on the mineral composition and microstructures. …”
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Cyber attack detection in IOT-WSN devices with threat intelligence using hidden and connected layer based architectures by S. Nandhini, A. Rajeswari, N. R. Shanker

“…Abstract In this paper, cyber-attacks in IOT-WSN are detected through proposed optimized-Neural Network algorithms such as (i) Equilibrium Optimizer Neural Network (EO-NN), (ii) Particle Swarm Optimization (PSO-NN), (iii) Single Candidate Optimizer Neural Network (SCO-NN) and (iv) Single Candidate Optimizer Long Short-Term Memory (SCO-LSTM) with different connecting, hidden neural network layers and threat intelligence data. …”
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Development of High Accuracy Classifier for the Speaker Recognition System by Raghad Tariq Al-Hassani, Dogu Cagdas Atilla, Çağatay Aydin

“…In order to enhance noise immunity, we proposed a single hidden layer feed-forward neural network (FFNN) tuned by an optimized particle swarm optimization (OPSO) algorithm. …”
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A Dynamic Processing System for Sensor Data in IoT by Minbo Li, Yanling Liu, Yuanfeng Cai

“…This paper proposes a dynamic sensor data processing (SDP) system to capture and process sensor data continuously on the basis of data streaming technology. Particle Swarm Optimization (PSO) algorithm is employed to train threshold dynamically for data compression avoiding redundancy. …”
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A Segmented Low-Order Bistable Stochastic Resonance Method for Fixed-Distance Target Detection in Millimeter-Wave Fuze Under Rainy Conditions by Bing Yang, Kaiwei Wu, Zhe Guo, Yanbin Liang, Shijun Hao, Zhonghua Huang

“…To address these limitations while satisfying real-time processing requirements, this study proposes (1) a novel segmented low-order bistable stochastic resonance (SLOBSR) system based on piecewise polynomial potential functions and (2) a corresponding fixed-distance target detection algorithm incorporating signal pre-processing, particle swarm optimization (PSO)-based parameter optimization, and kurtosis threshold detection. …”
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A dual-layer planning method based on improved MOPSO for distribution networks considering source–load temporal uncertainty by Guilian Wu, Guilian Wu, Jia Lin, Jinlin Liao

“…Third, an improved multi-objective particle swarm optimization (MOPSO) algorithm with adaptive inertia weights accelerates the convergence by 25%. …”
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Global Maximum Power Point Tracking of Photovoltaic Systems Using Artificial Intelligence by Rukhsar, Aidha Muhammad Ajmal, Yongheng Yang

“…According to the benchmarking, a modified particle swarm optimization (PSO) GMPPT algorithm is proposed, and the experimental results validate its ability to achieve GMPPT with faster dynamics and higher efficiency. …”
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Evaluation of a robust PID dead-time compensation controller based on the evolutionary computation method by Arun Ramaveerapathiran, R. Muniraj, T. Jarin, S.R. Boselin Prabhu, M. Willjuice Iruthayarajan

“…Tuning is performed by resolving an optimization issue in addition to constraints on robustness using efficient Heterogeneous Comprehensive Learning Particle Swarm Optimization (HCLPSO) evolutionary computation algorithm. …”
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Zoning Elastic Modulus Inversion for High Arch Dams Based on the PSOGSA-SVM Method by Bo Chen, Xiao Fu, Xuyuan Guo, Chongshi Gu, Chenfei Shao, Xiangnan Qin

“…The zoning elastic modulus of a high arch dam is inversed by using deformation safety monitoring data in the operation period, based on the particle swarm optimization with gravitation search algorithm for support vector machine (PSOGSA-SVM) method. …”
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Research on Coordinated Control of Dynamic Reactive Power Sources of DC Blocking and Commutation Failure Transient Overvoltage in New Energy Transmission by Shuqin Sun, Zhenghai Yuan, Dezhi Chen, Zaihua Li, Xiaojun Tang, Yunting Song, Guanghao Zhou

“…A multi-objective particle swarm optimization algorithm, incorporating comprehensive trajectory sensitivity and dynamically adaptive inertia weights, is introduced, alongside Pareto front theory, to achieve rapid and balanced optimization among competing objectives. …”
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Joint Allocation of Shared Yard Space and Internal Trucks in Sea–Rail Intermodal Container Terminals by Xiaohan Wang, Zhihong Jin, Jia Luo

“…A two-layer hybrid heuristic algorithm incorporating adaptive Particle Swarm Optimization and Greedy Rules is designed. …”
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An effective method for the abnormal monitoring of stage performance based on visual sensor network by Fuquan Zhang, Gangyi Ding, Lin Xu, Bo Chen, Zuoyong Li

“…Through the background subtraction, the weighted threshold-based segmentation of the target image from the background image, the chaotic search particle swarm optimization algorithm based on image target detection and tracking algorithm for target tracking by mean shift, the abnormal behavior of local linear embedding and detection method based on sparse representation, a comprehensive analysis of the local manifold structure of sample is set. …”
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Novel Approaches to Improve Iris Recognition System Performance Based on Local Quality Evaluation and Feature Fusion by Ying Chen, Yuanning Liu, Xiaodong Zhu, Huiling Chen, Fei He, Yutong Pang

“…Secondly, six local quality evaluation parameters are adopted to analyze texture information of each track. Besides, particle swarm optimization (PSO) is employed to get the weights of these evaluation parameters and corresponding weighted coefficients of different tracks. …”
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Performance evaluation of an adopted model based on big-bang big-crunch and artificial neural network for cloud applications by Pradeep Rawat, Robin Singh Bhadoria, Punit Gupta, Priti Dimri, G. P. Saroha

“…The proposed model is inspired from Big-Bang Big-Crunch algorithm in astrology. The work has been compared with a genetic algorithm, Particle swarm optimization and TOPSIS algorithm. …”
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Performance Evaluation of Intrusion Detection System using Selected Features and Machine Learning Classifiers by Raja Azlina Raja Mahmood, AmirHossien Abdi, Masnida Hussin

“…The two sets of selected features are based on Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) approach respectively.  …”
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Machine learning-based multiphysics model for corrosion fatigue crack propagation in aluminum alloy by Hongkun Wang, Zhenshuang Wu, Dongmei Jiang, Haitao Wang, En-Hou Han

“…In view of the complexity and nonlinearity of model parameter optimization, a particle swarm optimization algorithm was utilized to mutually feedback experimental measurement results with simulation results, optimizing the unknown parameters in the model to obtain a high-fidelity corrosion fatigue model. …”
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Green-fitting scheduling equilibrium model of virtual power plant based on cooperative game with improved shapley value under new-type power system by Shuo Zhang, Luming Pang, Yingzi Li, Yuanli Chen, Kangxiang Li, Meixia Zheng

“…To solve the model effectively, the improved particle swarm optimization algorithm has been employed. …”
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