A Feedback-Assisted Inverse Neural Network Controller for Cart-Mounted Inverted Pendulum by ManMahendra Singh Daksh, Puneet Mishra

“…Further, we have used a bio-inspired optimization algorithm, that is, particle swarm optimization (PSO), to optimize the initial weights of the INN along with the PID controller’s parameters to get an optimal control performance. …”
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Integration of Multi-Source Landslide Disaster Data Based on Flink Framework and APSO Load Balancing Task Scheduling by Zongmin Wang, Huangtaojun Liang, Haibo Yang, Mengyu Li, Yingchun Cai

“…The present study proposes an innovative approach to integrate multi-source landslide disaster data by combining the Flink-oriented framework with load balancing task scheduling based on an improved particle swarm optimization (APSO) algorithm. It utilizes Flink’s streaming processing capabilities to efficiently process and store multi-source landslide data. …”
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Coverage Hole Recovery in Hybrid Sensor Networks Based on Key Perceptual Intersections for Emergency Communications by He Li, Shixian Sun, Chuang Dong, Qinglei Qi, Cong Zhao, Zufeng Fu, Peng Yu, Jiajia Liu

“…Finally, the holes are recovered using the average of the key perceptual intersections as the initial value of the global optimal point of the particle swarm optimization algorithm. …”
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A Hybrid CNN-LSTM Model With Attention Mechanism for Improved Intrusion Detection in Wireless IoT Sensor Networks by Pendukeni Phalaagae, Adamu Murtala Zungeru, Abid Yahya, Boyce Sigweni, Selvaraj Rajalakshmi

“…To address computational demands, an enhanced Particle Swarm Optimization (PSO) algorithm is implemented for dynamic feature selection, thereby optimizing the system’s efficiency in high-dimensional data environments characteristic of IoT networks. …”
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Enhancing 4G/LTE Network Path Loss Prediction with PSO-GWO Hybrid Approach by Messaoud Garah, Nabil Boukhennoufa

“…The best model for estimating the measured path loss is then optimized using three well-known evolutionary algorithms: Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO), and Covariance Matrix Adaptation Evolution Strategy (CMA-ES). …”
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A Systematic Mapping Study on State Estimation Techniques for Lithium-Ion Batteries in Electric Vehicles by Carolina Tripp-Barba, José Alfonso Aguilar-Calderón, Luis Urquiza-Aguiar, Aníbal Zaldívar-Colado, Alan Ramírez-Noriega

“…The findings disclose various methods that boost the accuracy and reliability of SoC, including enhanced variants of the Kalman filter, machine learning models like long short-term memory (LSTM) and convolutional neural networks (CNNs), as well as hybrid optimization frameworks that combine Grey Wolf Optimization (GWO) and Particle Swarm Optimization (PSO). …”
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UAV Robust Strategy Control Based on MAS by Jian Han, Changhong Wang, Guoxing Yi

“…The MAS uses BDI model to support its logical perception and to classify the different missions; then the missions will be allocated by utilizing auction mechanism after analyzing dynamic parameters. Prim potential algorithm, particle swarm algorithm, and reallocation mechanism are proposed to realize the rational decomposing and optimal allocation in order to reach the maximum profit. …”
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Composite fault feature extraction for gears based on MCKD-EWT adaptive wavelet threshold noise reduction by Yanchang LV, Jingyue Wang, Chengqiang Zhang, Jianming Ding

“…Firstly, envelope entropy and information entropy are used as fitness functions, and the parameters of the MCKD algorithm are optimized by the improved particle swarm algorithm, then the empirical wavelet decomposition is carried out on the signals, and finally adaptive wavelet threshold denoising is carried out on the decomposed Intrinsic mode functions (IMFs) components. …”
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A Comprehensive Survey on AI in Counter-Terrorism and Cybersecurity: Challenges and Ethical Dimensions by Ioannis Syllaidopoulos, Klimis S. Ntalianis, Ioannis Salmon

“…This paper provides a comprehensive overview of AI methodologies, such as predictive analytics, Natural Language Processing (NLP), and machine learning architectures (e.g., Support Vector Machines – SVM and Long Short-Term Memory – LSTM), and optimization algorithms (e.g., Particle Swarm Optimization – PSO), assessing their effectiveness in security applications. …”
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Approaches for handling imbalanced data used in machine learning in the healthcare field: A case study on Chagas disease database prediction. by André G Coimbra, Cleiane G Oliveira, Matheus P Libório, Hasheem Mannan, Laercio I Santos, Elisa Fusco, Marcos F S V D'Angelo

“…Additionally, a new approach based on Particle Swarm Optimization (PSO) and Naive Bayes was proposed. …”
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A survey on PSO based meta-heuristic scheduling mechanism in cloud computing environment by Arabinda Pradhan, Sukant Kishoro Bisoy, Amardeep Das

“…In this paper a systematically reviews is done on different types of particle swarm optimization (PSO) based scheduling strategy with set of challenges and future direction.…”
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Similar Instances Reuse Based Numerical Control Process Decision Method for Prismatic Parts by Changhong XU, Shusheng ZHANG, Jiachen LIANG, Rui HUANG, Rong BIAN

“…In addition, the existing NC process decision methods, such as the genetic algorithm, ant colony algorithm, and particle swarm algorithm, have not been combined with the reuse approach. …”
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Control Research on Active Pitch Control System for Horizontal-Axis Tidal-Current Turbine Generator by Fuli Zhang, Wanqiang Zhu, Shuai Zu, Xueming Zhang, Jianmei Chen, Baigong Wu, Jipeng Huang

“…The application of a particle swarm optimization (PSO)–PID controller and fuzzy PID controller in the independent interval system of tidal generator sets is introduced for the first time in this paper. …”
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Smart grid stability prediction model using two-way attention based hybrid deep learning and MPSO by Umesh Kumar Lilhore, Surjeet Dalal, Magdalena Radulescu, Marinela Barbulescu

“…This research presents a hybrid deep learning model (Convolutional Neural Network [CNN] with Bi-LSTM) with a two-way attention method and a multi-objective particle swarm optimization method (MPSO) for short-term load prediction from a smart grid. …”
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Inverse-Designed Ultra-Compact Passive Phase Shifters for High-Performance Beam Steering by Tianyang Fu, Mengfan Chu, Ke Jin, Honghan Sha, Xin Yan, Xueguang Yuan, Yang’an Zhang, Jinnan Zhang, Xia Zhang

“…Ultra-compact passive phase shifters are inversely designed by the multi-objective particle swarm optimization algorithm. The wavelength-dependent phase difference between two output beams originates from the different distances of the input light passing through the 4 μm × 3.2 μm rectangular waveguide with random-distributed air-hole arrays. …”
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Rockburst Prediction Based on the KPCA-APSO-SVM Model and Its Engineering Application by Yuefeng Li, Chao Wang, Jiankun Xu, Zonghong Zhou, Jianhui Xu, Jianwei Cheng

“…Based on the kernel principal component analysis (KPCA), the adaptive particle swarm optimization (APSO) algorithm, and the support vector machine (SVM), the KPCA-APSO-SVM model was established. …”
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A Crash Severity Prediction Method Based on Improved Neural Network and Factor Analysis by Chen Zhang, Jie He, Yinhai Wang, Xintong Yan, Changjian Zhang, Yikai Chen, Ziyang Liu, Bojian Zhou

“…Data from I5, an interstate highway in the Washington State during the period of 2011–2015, were used for fitting and prediction, and after setting the theoretical three-layer neural network (NN), an improved Particle Swarm Optimization (PSO) method with adaptive inertial weight was offered to optimize the NN, and finally, a comparison among different adaptive strategies was conducted. …”
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Analysis of the Impact and Weight of Structural Parameters on the Operating Characteristics of the Spring Operating Mechanism by Qi Long, Xu Yang, Keru Jiang, Changhong Zhang, Xiao Wang, Xiongying Duan

“…Finally, based on the influence weights, a sensitivity-adaptive particle swarm optimization algorithm was developed to optimize the spring-operated mechanism, reducing its failure probability by 16.67%, which is beneficial for the design of controlled switching algorithms.…”
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Comparing machine learning approaches for estimating soil saturated hydraulic conductivity. by Ali Akbar Moosavi, Mohammad Amin Nematollahi, Mohammad Omidifard

“…Then, radial basis functions (RBFNNs), multilayer perceptron (MLPNNs), hybrid genetic algorithm (GA-NNs), and particle swarm optimization (PSO-NNs) neural networks were utilized to develop PTFs and compared their accuracy with the traditional regression model (MLR) using statistical indices. …”
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Design of a Deep Learning-Based Metalens Color Router for RGB-NIR Sensing by Hua Mu, Yu Zhang, Zhenyu Liang, Haoqi Gao, Haoli Xu, Bingwen Wang, Yangyang Wang, Xing Yang

“…In this study, we propose a deep learning network capable of forward prediction across a broad wavelength range, combined with a particle swarm optimization algorithm to design metalens efficiently. …”
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