Fluid–Structure Interaction Study in Unconventional Energy Horizontal Wells Driven by Recursive Algorithm and MPS Method by Xikun Gao, Dajun Zhao, Yi Zhang, Yong Chen, Zhanzhao Gao, Xiaojiao Zhang, Shengda Wang

“…This study presents a novel bidirectional fluid–structure interaction (FSI) model, uniquely integrating recursive algorithms with the Moving Particle Semi-implicit (MPS) method to couple drill string–wellbore contact with drilling fluid interactions. …”
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Research on Health Monitoring of Flying-Swallow-Typed Tied Arch Bridge Based on PSO-GRNN Algorithm by Tianpeng Zhang, Long Liu, Pengfei Ji

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Optimizing Artificial Neural Network Learning Using Improved Reinforcement Learning in Artificial Bee Colony Algorithm by Taninnuch Lamjiak, Booncharoen Sirinaovakul, Siriwan Kornthongnimit, Jumpol Polvichai, Aysha Sohail

“…Enhanced R-ABC and PSO algorithms can significantly improve ANN training performance and efficiency, especially in complex and high-dimensional datasets.…”
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Data-driven continuous-time Hammerstein modeling with missing data using improved Archimedes optimization algorithm by Muhammad Shafiqul Islam, Mohd Ashraf Ahmad

“…Across all experiments, the IAOA-based method demonstrated superior performance compared to AOA and other methods, including a hybrid approach combining the average multi-verse optimizer and sine cosine algorithm, particle swarm optimizer, the sine cosine algorithm, multi-verse optimizer and grey wolf optimizer. …”
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Classification Prediction of Jujube Variety Based on Hyperspectral Imaging: A Comparative Study of Intelligent Optimization Algorithms by Quancheng Liu, Jun Zhou, Zhaoyi Wu, Didi Ma, Yuxuan Ma, Shuxiang Fan, Lei Yan

“…This study integrates hyperspectral imaging with intelligent optimization algorithms—Zebra Optimization Algorithm (ZOA), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Grey Wolf Optimization (GWO)—and a Support Vector Machine (SVM) model to classify jujube varieties. …”
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Optimization of Fuzzy Adaptive Logic Controller for Robot Manipulators Using Modified Greater Cane Rat Algorithm by Jian Sun, Shuyi Wu, Jinfu Chen, Xingjia Li, Ziyan Wu, Ruiting Xia, Wei Pan, Yan Zhang

“…For benchmarking, several state-of-the-art swarm intelligence algorithms—including particle swarm optimization (PSO), artificial bee colony (ABC), ant colony optimization (ACO), gray wolf optimization (GWO), covariance matrix adaptation evolution strategy (CMA-ES), adaptive guided differential evolution (AGDE), the basic greater cane rat algorithm (GCRA), and a trial-and-error method—are compared under identical conditions. …”
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Reliability Analysis of a Direct Shear Test of Modified Iron Tailings Based on the Monte Carlo Algorithm by Ping Jiang, Jian Qian, Na Li

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Email Spam Detection Using a Hybrid Approach of Feedforward Neural Network and Penguin Optimization Algorithm by Layth Al-busultan

“…The POA is a powerful optimization algorithm that can perform very well when fine-tuning the weights and biases of a neural network. …”
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Using crafted features and polar bear optimization algorithm for short-term electric load forecast system by Mansi Bhatnagar, Gregor Rozinaj, Radoslav Vargic

“…PBO was compared with commonly used optimization algorithms like particle swarm optimization (PSO) and genetic algorithm (GA). …”
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Intelligent recognition algorithm and application of coal mine overhead passenger device based on multiscale feature fusion by Beijing XIE, Heng LI, Hang DONG, Zheng LUAN, Ben ZHANG, Xiaoxu LI

“…Partial implementation approaches for deploying the video media stream into the cmopd intelligent recognition system were provided. …”
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Multi-objective portfolio optimization using real coded genetic algorithm based support vector machines by B. Surja, L. Chin, F. Kusnadi

“…Single optimal portfolios were created using the real coded genetic algorithm based on different sets of objectives: Maximizing short-term and long-term returns, maximizing liquidity, and minimizing risk. …”
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Application of M5 algorithm of decision tree in simulation and investigation of effective factors of erosion in rangelands and forests by Hatem Ghaleb Maabreh, Khlood Waheeb, Abrar Ryadh, Saja Basheer Abdulghani, Zainab Jamal Hamoodah, Nisreen Yasir Jasim, Fakhri Alajeeli, Ali H. O. Al Mansor, Mikhail Andreevich

“…The aim of this paper was to identify the factors affecting interrill erosion using the M5 algorithm of decision tree in four different regions. …”
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Adaptive energy loss optimization in distributed networks using reinforcement learning-enhanced crow search algorithm by S. Bharath, A. Vasuki

“…Unlike traditional methods such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and standard Crow Search Algorithm (CSA), which suffer from premature convergence and limited adaptability to real-time variations, Reinforcement Learning Enhanced Crow Search Algorithm (RL-CSA) which is proposed in this research work solves network reconfiguration optimization problem and minimize energy losses. …”
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Multi-Objective Optimization for the Low-Carbon Operation of Integrated Energy Systems Based on an Improved Genetic Algorithm by Yao Duan, Chong Gao, Zhiheng Xu, Songyan Ren, Donghong Wu

“…We compared its performance against a multi-objective genetic algorithm, a multi-objective particle swarm algorithm, and a single-objective genetic algorithm. …”
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A Comparative Study between Different Machine Learning Algorithms for Estimating the Vehicular Delay at Signalized Intersections by Yazan Alatoom, Abdallah Al-Hamdan

“…Consequently, this study aimed to compare a wide array of machine learning algorithms, including Artificial Neural Networks (ANN), Random Forest (RF), decision tree, Support Vector Machine (SVM), K-Nearest Neighbor (K-NN), AdaBoost, Gradient Boost, XGBoost, and Partial Least Squares (PLS) regression. …”
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GCS-YOLO: A Lightweight Detection Algorithm for Grape Leaf Diseases Based on Improved YOLOv8 by Qiang Hu, Yunhua Zhang

“…In view of the issues of high complexity, significant computational resource consumption, and slow inference speed in the detection algorithm for grape leaf diseases, this paper proposes GCS-YOLO, a lightweight detection algorithm based on an improved YOLOv8. …”
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Optimizing machine learning algorithms for diabetes data: A metaheuristic approach to balancing and tuning classifiers parameters by Hauwau Abdulrahman Aliyu, Ibrahim Olawale Muritala, Habeeb Bello-Salau, Salisu Mohammed, Adeiza James Onumanyi, Ore-Ofe Ajayi

“…Leveraging Particle Swarm Optimization (PSO) algorithm for diabetes data balancing and a genetic algorithm to select the optimal architecture for various machine learning classifiers. …”
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An efficient algorithm for pedestrian fall detection in various image degradation scenarios based on YOLOv8n by Jianhui Xun, Xuefeng Wang, Xiufang Wang, Xiaoliang Fan, Peishuai Yang, Zhifei Zhang

“…To address these issues, this paper proposes an enhanced pedestrian fall detection algorithm called Pedestrian Chain-of-Thought Prompted Adaptive Enhancer YOLO (PCE-YOLO), based on YOLOv8n. …”
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Applications of Metaheuristic Algorithms in Solar Air Heater Optimization: A Review of Recent Trends and Future Prospects by Jean De Dieu Niyonteze, Fumin Zou, Godwin Norense Osarumwense Asemota, Walter Nsengiyumva, Noel Hagumimana, Longyun Huang, Aphrodis Nduwamungu, Samuel Bimenyimana

“…In the paper, we do not only discuss the techniques used to enhance the performance of SAHs, but we also reviewed a majority of published papers on the applications of SAH optimization. The metaheuristic algorithms include simulated annealing (SA), particle swarm optimization (PSO), genetic algorithm (GA), artificial bee colony (ABC), teaching-learning-based optimization (TLBO), and elitist teaching-learning-based optimization (ETLBO). …”
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Optimizing Battery Charging in Wireless Sensor Networks: Performance Assessment of MPPT Algorithms in Different Environmental Settings by Abdullah Fadhil Noor Shubbar, Serkan Savaş, Osman Güler

“…Given the critical role of battery performance in WSN reliability, efficient energy management through Maximum Power Point Tracking (MPPT) algorithms is essential to adapt to variable environmental conditions such as solar irradiance and ambient temperature.Objective: This study aims to comparatively assess the performance of four widely adopted MPPT algorithms-Perturb and Observe (P&O), Incremental Conductance (IC), Fuzzy Logic (FL), and Particle Swarm Optimization (PSO)-in enhancing battery charging efficiency in PV-powered WSNs under dynamic environmental conditions.Methods: A simulation-based evaluation framework was developed using MATLAB/Simulink to model a PV-powered WSN system. …”
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