Artificial intelligence-based Bayesian optimization and transformer model for tennis motion recognition by Shaowei Shi, Kun Huang

“…A human key point recognition algorithm is designed based on Transformer. Then, the optimal pruning rate of each layer of the network is found by using Bayesian optimization algorithm to improve the efficiency and accuracy of subnet search. …”
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Biomechanical Modeling of Selected Methods of Load Carriage to Improve Military Capabilities of Troops by Mostafa Hajlotfalian, Alireza Redaei, Heydar Sadeghi

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Predicting the chemical equilibrium point of reacting components in gaseous mixtures through a novel Hierarchical Manta-Ray Foraging Optimization Algorithm by Oguz Emrah Turgut, Hadi Genceli, Mustafa Asker, Mustafa Turhan Çoban, Mohammad Akrami

“…To improve the solution diversity in the trial Manta-Ray population and enhance the general optimization effectivity of the algorithm, an ordered hierarchy is integrated into the original algorithm, taking into account the efficient search strategies of Elite-Opposition learning, Dynamic Opposition Learning, and Quantum search operator. …”
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Improving parking availability prediction in smart cities with IoT and ensemble-based model by Stéphane Cédric Koumetio Tekouabou, El Arbi Abdellaoui Alaoui, Walid Cherif, Hassan Silkan

“…We propose in this paper a new system that integrates the IoT and a predictive model based on ensemble methods to optimize the prediction of the availability of parking spaces in smart parking. …”
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Modeling and Optimization of Beam Pumping System Based on Intelligent Computing for Energy Saving by Xiaohua Gu, Taifu Li, Zhiqiang Liao, Liping Yang, Ling Nie

“…It firstly employs the general regression neural network (GRNN) algorithm to obtain the best model of the beam pumping system, and secondly searches the optimal operation parameters with improved strength Pareto evolutionary algorithm (SPEA2). …”
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Precision evaluation criteria for simulation algorithms in infinite systems: A network model-based approach by Yonglong Ding

“…As the particle count escalates, the computational demands of diverse simulation algorithms surge, paralleled by a marked improvement in accuracy. …”
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A SA-ANN-Based Modeling Method for Human Cognition Mechanism and the PSACO Cognition Algorithm by Shuting Chen, Dapeng Tan

“…Firstly, the relationship between SA processing procedure and cognition knowledge evolution is analyzed, and a SA-ANN-based inference model is set up. Then, based on the inference model, a Powell SA with combinatorial optimization (PSACO) algorithm is proposed to improve the clustering efficiency and recognition accuracy for the cognition process. …”
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Postpartum depression risk prediction using explainable machine learning algorithms by Xudong Huang, Lifeng Zhang, Chenyang Zhang, Jing Li, Chenyang Li

“…Feature selection was performed using LASSO regression and the Boruta algorithm. Eight machine learning algorithms were then employed to construct the prediction models. …”
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Review of Icing Prediction Model and Algorithm for Overhead Transmission Lines Considering Time Cumulative Effects by Chuanqi WANG, Liwen WU, Zhibin DENG, Weifeng DENG, Bin YANG

“…Secondly, the combination and intercrossing mode of support vector machine, hybrid swarm intelligence optimization algorithm, genetic algorithm in the model focus on the identification and modeling of icing process. …”
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COD Optimization Prediction Model Based on CAWOA-ELM in Water Ecological Environment by Lili Jiang, Liu Yang, Yang Huang, Yi Wu, Huixian Li, XiYan Shen, Meng Bi, Lin Hong, Yiting Yang, Zuping Ding, Wenjie Chen

“…In order to detect high error rate and poor convergence of the water ecological chemical oxygen demand (COD) prediction model, combining the limit learning machine (ELM) model and whale optimization algorithm, CAWOA is improved by the sin chaos search strategy, while the ELM optimizes the parameters of the algorithm to improve convergence speed, thus improving the generalization performance of the ELM. …”
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Advanced predictive disease modeling in biomedical IoT using the temporal adaptive neural evolutionary algorithm by Chandragandhi S, Arvind C, Srihari K

“…TANEA leverages temporal data patterns, adapts to dynamic changes in sensor readings, and optimizes feature selection through an evolutionary mechanism, resulting in a more precise and reliable predictive model. …”
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Multibranch semantic image segmentation model based on edge optimization and category perception. by Zhuolin Yang, Zhen Cao, Jianfang Cao, Zhiqiang Chen, Cunhe Peng

“…Second, a category perception module is used to learn category feature representations and guide the pixel classification process through an attention mechanism to optimize the resulting segmentation accuracy. Finally, an edge optimization module is used to integrate the edge features into the middle and the deep supervision layers of the network through an adaptive algorithm to enhance its ability to express edge features and optimize the edge segmentation effect. …”
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Optimized actuator design for flapping-wing robots: A multi-objective approach to mimic natural flapping dynamics by Peiqi Li, Zhiwei Ai, Mufan Zhang

“…The optimization utilized the NSGA-II algorithm. Additionally, a virtual prototype with rigid-flexible coupling was created for simulation assessments pre- and post-optimization. …”
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Bayesian optimization of hybrid quantum LSTM in a mixed model for precipitation forecasting by Yumin Dong, Huanxin Ding

“…The hyperparameters of the model are optimized using the Bayesian optimization algorithm to obtain the best performance. …”
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Phase Sequence Adjustment Method for Three-Phase Load Imbalance in Station Area Based on Improved Pigeon-inspired Optimization by Mingyue HU, Huifen ZHANG, Shuping MIAO, Fan YANG, Zhenming QU

“…The unbalanced load commutation control strategy is used to establish an optimal commutation mathematical model with the goal of minimizing the three-phase current imbalance on the low-voltage side of the distribution transformers; the adaptive parameters and Cauchy disturbance are introduced to improve the original pigeon-inspired optimization (PIO) algorithm. …”
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Multiradar Collaborative Task Scheduling Algorithm Based on Graph Neural Networks with Model Knowledge Embedding by Haoqing LI, Dian YU, Changchun PAN, Wenxian YU, Dongying LI

“…A key innovation of this algorithm is its capability to capture critical model knowledge using low-complexity calculations, which helps to further optimize the GNN model. …”
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A combined model of shoot phosphorus uptake based on sparse data and active learning algorithm by Tianli Wang, Yi Zhang, Haiyan Liu, Fei Li, Dayong Guo, Ning Cao, Yubin Zhang

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A multi-algorithm prognostic model combining inflammatory indices and surgical features in distal cholangiocarcinoma by Yi Yin, Yi Yin, Luyuan Bai, Xinyue Mu, Xinyue Mu, Shan Zhang, Panpan Zhai, Panpan Zhai

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Detection Model for Cotton Picker Fire Recognition Based on Lightweight Improved YOLOv11 by Zhai Shi, Fangwei Wu, Changjie Han, Dongdong Song, Yi Wu

“…The improved detection algorithm maintains high accuracy while achieving faster inference speed and fewer model parameters. …”
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Frequency regulation of two-area thermal and photovoltaic power system via flood algorithm by Serdar Ekinci, Davut Izci, Cebrail Turkeri, Aseel Smerat, Absalom E. Ezugwu, Laith Abualigah

“…The implementation details of the FLA-tuned PI controller are provided, and its performance is rigorously compared with PI controllers tuned using several state-of-the-art optimization techniques. These include sea horse optimization, salp swarm algorithm, whale optimization algorithm, shuffled frog-leaping algorithm, and firefly algorithm. …”
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