A Simple Method for Correcting Empirical Model Densities During Geomagnetic Storms Using Satellite Orbit Data by Daniel A. Brandt, Charles D. Bussy‐Virat, Aaron J. Ridley

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Establishment of Hyperspectral Prediction Model of Water Content in Anshan-Type Magnetite by Xiaoxiao XIE, Yang BAI, Jiuling ZHANG, Yuna JIA

“…In order to further improve the prediction ability of the model, the competitive adaptive reweighting method (CARS) was used to optimize the characteristic band, and a prediction model was established by combining random forest regression (RFR), least squares support vector regression (LSSVR) and particle swarm optimization least squares support vector regression (PSO-LSSVR). …”
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Synergistic effect of artificial intelligence and new real-time disassembly sensors: Overcoming limitations and expanding application scope by Bozhou Li, Dajiang Ju, Xingwang Li, Yan Liu, Hongru He, Hao Wang

“…Then, based on the gated recurrent unit (GRU) model, the article applied the particle swarm optimization (PSO) algorithm to optimize the parameters of the GRU network and used the support vector machine (SVM) model to optimize the classification function of the network output. …”
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Digital Twin Driven Four-Dimensional Path Planning of Collaborative Robots for Assembly Tasks in Industry 5.0 by Ilias Chouridis, Gabriel Mansour, Asterios Chouridis, Vasileios Papageorgiou, Michel Theodor Mansour, Apostolos Tsagaris

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A multi-objective metaheuristic method for node placement in dynamic IoT environments by Farzad Kiani

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Prediction of compressive strength and characteristics analysis of semi-flexible pavement desert sand grouting material based upon hybrid-BP neural network by Wenbang Zhu, Yuhang Li, Xiumei Zheng, Enze Hao, Dali Zhang, Zhen Wang

“…To precisely obtain DSGM exhibiting exceptional mechanical properties, the Backpropagation Neural Network (BPNN) model was optimized through the utilization of Particle Swarm Optimization (PSO), Sparrow Search Algorithm (SSA), and Genetic Algorithm (GA). …”
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A Predictive Method for Greenhouse Soil Pore Water Electrical Conductivity Based on Multi-Model Fusion and Variable Weight Combination by Jiawei Zhao, Peng Tian, Jihong Sun, Xinrui Wang, Changjun Deng, Yunlei Yang, Haokai Zhang, Ye Qian

“…We propose a hybrid prediction model—PSO–CNN–LSTM–BOA–XGBoost (PCLBX)—that integrates a particle swarm optimization (PSO)-enhanced convolutional LSTM (CNN–LSTM) with a Bayesian optimization algorithm-tuned XGBoost (BOA–XGBoost). …”
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Berth Allocation and Quay Crane Assignment Considering the Uncertain Maintenance Requirements by Siwei Li, Liying Song

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Integrated intrusion detection design with discretion of leading agent using machine learning for efficient MANET system by K. S. Nirmala Bai, Dr M.V. Subramanyam

“…Particle Swarm Optimization (PSO) is defined for the initial clustering of nodes and immediately the O-MLM is performed to detect the leading agent nodes in each cluster with the selection features of node degree, node mobility, energy, distance and delay. …”
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Analysis of the Trends and Driving Factors of Cultivated Land Utilization Efficiency in Henan Province from 2000 to 2020 by Henggang Zhang, Chenhui Zhu, Tianyu Jiao, Kaiyue Luo, Xu Ma, Mingyu Wang

“…Additionally, we used a genetic algorithm optimized Artificial Neural Network (ANN) and a particle swarm optimization-based Random Forest (RF) model to assess the comprehensive in-fluence between topography, climate, and human activities on CLUE, in which incorporating Shapley Additive Explanations (SHAP) values. …”
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Comparative Evaluation of Fractional-Order Models for Lithium-Ion Batteries Response to Novel Drive Cycle Dataset by Xinyuan Wei, Longxing Wu, Chunhui Liu, Zhiyuan Si, Xing Shu, Heng Li

“…First, three typical FOMs were initially established and the particle swarm optimization algorithm was then employed to identify model parameters. …”
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InBRwSANet: Self-attention based parallel inverted residual bottleneck architecture for human action recognition in smart cities. by Yasir Khan Jadoon, Muhammad Attique Khan, Yasir Noman Khalid, Jamel Baili, Nebojsa Bacanin, MinKyung Hong, Yunyoung Nam

“…The proposed architecture is trained on the selected datasets, whereas the hyperparameters are chosen using the particle swarm optimization (PSO) algorithm. The trained model is employed in the testing phase for the feature extraction from the self-attention layer and passed to the shallow wide neural network classifier for the final classification. …”
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Neural network backstepping control of OWC wave energy system by Priyanka Nath, Sunil Kumar Mishra, Amitkumar Vidyakant Jha, Bhargav Appasani, Akshaya Kumar Pati, Vijay Kumar Verma, Philibert Nsengiyumva, Avireni Srinivasulu

“…The parameters for PI, BSC, and NN-BSC are optimized using a Particle Swarm Optimization (PSO) algorithm, which minimizes a fitness function defined by the Integral Squared Error (ISE). …”
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A multistate transition model for survival estimation in randomized trials with treatment switching and a cured subgroup by Haixia Hu, Ling Wang, Kejian Wu, Wei Ge, Jielai Xia, Chen Li

“…Meanwhile, the semi-competing risks model is used for the treatment effect evaluation on the uncured patients through transitional hazards between states of PD, treatment switching, and death. The particle swarm optimization algorithm is employed to estimate the model parameters. …”
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Key technologies of robotic arm motion control based on compound control and improved SCSO. by Kuo Hu

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A Novel Remote Sensing Recognition Using Modified GMM Segmentation and DenseNet by Muhammad Waqas Ahmed, Moneerah Alotaibi, Sultan Refa Alotaibi, Dina Abdulaziz Alhammadi, Asaad Algarni, Ahmad Jalal, Jeongho Cho

“…These features are fused and refined using Particle Swarm Optimization (PSO) to create a robust and informative representation. …”
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Hybrid Active and Passive Cable Contour Shielding of Magnetic Fields of Double-Circuit Overhead Power Lines by Kuznetsov B.I., Kutsenko A.S., Nikitina T.B.

“…The solution to the minimax vector optimization problem is calculated based on multi-particle swarm optimization algorithms from Pareto-optimal solutions taking into account binary preference relations. …”
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A PSO weighted ensemble framework with SMOTE balancing for student dropout prediction in smart education systems by Achin Jain, Arun Kumar Dubey, Shakir Khan, Arvind Panwar, Mohammad Alkhatib, Abdulaziz M Alshahrani

“…To address this, we propose a Particle Swarm Optimization (PSO)-Weighted Ensemble Framework integrated with the Synthetic Minority Oversampling Technique (SMOTE). …”
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Inversion model of stress state reconstruction for geological hazard pipelines based on digital twin by Xue Luning, Tian Mingliang, Zhao Juncheng

“…The mechanical state of the physical pipeline is mapped in real time by the digital twin, the numerical simulation and multi-source monitoring data are integrated, and the parameters of the twin model are dynamically optimized by combining the optimization algorithms of Particle Swarm Optimization (PSO) and Support Vector Machine (SVM), so as to realize the real-time prediction of the pipeline stress state and the dynamic updating of the disaster scenario. …”
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A novel approach for predicting the standardised precipitation index considering climatic factors by Mustafa A. Alawsi, Salah L. Zubaidi, Laith B. Al-badranee

“…., tolerance technique), in addition to, artificial neural network (ANN) combined with particle swarm optimisation (PSO)). The data on climatic factors were applied to build and evaluate the SPI 3 model from 1990 to 2020 for the Al-Kut region. …”
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