Vortex-Induced Vibration Performance Prediction of Double-Deck Steel Truss Bridge Based on Improved Machine Learning Algorithm by Yang Yang, Huiwen Hou, Gang Yao, Bo Wu

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Evolutionary Neural Simulation of Import Substitution in the Radio Electronics Industry in the Regions Using Adaptive Network-Based Fuzzy Inference System by Sergei Yashin, Egor Koshelev, Alexey Ivanov, Sergei Borisov, Diyor Karimov, Ivan Babkin

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SASDL and RBATQ: Sparse Autoencoder With Swarm Based Deep Learning and Reinforcement Based Q-Learning for EEG Classification by Sunil Kumar Prabhakar, Seong-Whan Lee

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BS-SCRM: a novel approach to secure wireless sensor networks via blockchain and swarm intelligence techniques by Jing Xiao, Chaoqun Li, Zhigang Li, Jie Zhou

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Risk prediction of hyperuricemia based on particle swarm fusion machine learning solely dependent on routine blood tests by Min Fang, Chengjie Pan, Xiaoyi Yu, Wenjuan Li, Ben Wang, Huajian Zhou, Zhenying Xu, Genyuan Yang

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Advanced intrusion detection technique (AIDT) for secure communication among devices in internet of medical things (IoMT) by M. Ramya, Pradeep Sudhakaran, Yuvaraj Sivagnanam, C. Santhana Krishnan

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A novel hybrid extreme learning machine-based diagnosis model for sensor node faults in aquaculture by Bing Shi, Zelin Gao, Tianheng Pu, Jianming Jiang, Yueping Sun

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TAE Predict: An Ensemble Methodology for Multivariate Time Series Forecasting of Climate Variables in the Context of Climate Change by Juan Frausto Solís, Erick Estrada-Patiño, Mirna Ponce Flores, Juan Paulo Sánchez-Hernández, Guadalupe Castilla-Valdez, Javier González-Barbosa

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A Hybrid Approach of DenseNet121 with Attention and Bi-LSTM for Yoga Pose Estimation by Aarthy K., Alice Nithya

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Optimum Design of a Photovoltaic Inverter System Based on Ga, Pso and Gwo Algorithms with a Mppt Sliding Mode Control by Alberto Coronado-Mendoza, Mónica Camas-Náfate, Jesús Sergio Artal-Sevil, José Antonio Domínguez-Navarro

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Prediction and reliability analysis of rigid pipeline response in soft soil using improved particle swarm neural network by Laifu Song, Shun Zhang, Jun Wang, Hongtao Fu, Jiayu Cai

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Adaptive Multi-Objective Firefly Optimization for Energy-Efficient and QoS-Aware Scheduling in Distributed Green Data Centers by Ahmed Chiheb Ammari, Wael Labidi, Rami Al-Hmouz

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A hybrid renewable energy system for Hassi Messaoud region of Algeria: Modeling and optimal sizing by Yacine Bourek, El Mouatez Billah Messini, Chouaib Ammari, Mohamed Guenoune, Boulerbah Chabira, Bipul Krishna Saha

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Charge and discharge scheduling method for large-scale electric vehicles in V2G mode via MLGCSO by Songling Pang, Kaidi Fan, Meiyi Huo

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Enhancing DC Motor Speed Control Performance Using Heuristic Optimization and Comparative Analysis of Control Methods by Ali Öztürk, Nasser Bandar Nasser Al Saremi, Beytullah Bozali

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Time frequency analysis of elastic wave PSO OMP for defects in flat steel of down conductors by Jing Zhang, Wei Liu, Minghui Bao, Peng Yang, Xuhua Liu, Zhihong Fu

“…To solve this problem, this paper uses the Particle Swarm Optimization Orthogonal Matching Pursuit (PSO-OMP) algorithm to reconstruct the signal, significantly reducing noise. …”
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Hybrid extreme learning machine for real-time rate of penetration prediction by Abdelhamid Kenioua, Omar Djebili, Ammar Touati Brahim

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Impact of solid oxide FC-RFB and IPFC on a renewable multi-area power system using combined PI and FOPD controllers optimized by the African Vulture algorithm by Arindita Saha, Mahajan Sagar Bhaskar, Mahmoud F. Elmorshedy, Dhafer J. Almakhles, Sanjeevikumar Padmanaban

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A Computational Intelligence Framework Integrating Data Augmentation and Meta-Heuristic Optimization Algorithms for Enhanced Hybrid Nanofluid Density Prediction Through Machine and... by Priya Mathur, Hammad Shaikh, Farhan Sheth, Dheeraj Kumar, Amit Kumar Gupta

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Investigation on Photovoltaic Array Modeling and the MPPT Control Method under Partial Shading Conditions by Jianbo Bai, Leihou Sun, Rupendra Kumar Pachauri, Guangqing Wang

“…Its main idea is to determine the initial position of particles and remove the acceleration factor and random number in traditional particle swarm optimization (PSO) algorithm. Additionally, according to the distance between two consecutive peak points, the maximum value of velocity is obtained. …”
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