GRL-ITransformer: An Intelligent Method for Multi-Wind-Turbine Wake Analysis Based on Graph Representation Learning With Improved Transformer by Kang Han, Li Xu

“…In our study, we propose a graph representation learning model with improved Transformer (GRL-ITransformer) to better integrate feature information, so that the model can capture the dynamic time relationship of different variables and establish its spatial relationship, striving to enhance the precision in predicting wind turbine wake field. …”
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Optimizing an LSTM Self-Attention Architecture for Portuguese Sentiment Analysis Using a Genetic Algorithm by Daniel Parada, Alexandre Branco, Marcos Silva, Fábio Mendonça, Sheikh Mostafa, Fernando Morgado-Dias

“…To address this complexity, a discrete genetic algorithm was used to find an optimal configuration, selecting the layer types, placement of self-attention, dropout rate, and model dimensions and shape. …”
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Optimization of Table Tennis Swing Action Supported by the Temporal Convolutional Network Algorithm in Deep Learning by Shaoxuan Sun, Hongyu Zheng, Zhixin Lin

“…To enhance the navigation accuracy and interpretability of Unmanned Aerial Vehicles (UAVs) in sports analysis, this study proposes an improved model based on the Temporal Convolutional Network (TCN) algorithm, integrated with Explainable Artificial Intelligence. …”
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Optimizing the light gradient-boosting machine algorithm for an efficient early detection of coronary heart disease by Temidayo Oluwatosin Omotehinwa, David Opeoluwa Oyewola, Ervin Gubin Moung

“…Findings: The optimized LightGBM model showed significant improvement in early CHD detection. …”
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Optimization of the Hollow Rectification Sill in the Forebay of the Pump Station Based on the PSO-GP Collaborative Algorithm by Wang Xi, Weigang Lu, Chuan Wang, Bo Xu

“…The layout of the pump station is easily affected by topography, site, and other factors, resulting in poor inlet flow patterns in the forebay, which seriously affect the normal operation of the pump station. To optimize its inlet flow pattern, the size of the hollow rectification sill has been continuously improved through physical model tests to meet the requirements of the required pump station inlet flow field. …”
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Enhanced Network Traffic Classification Using Bayesian-Optimized Logistic Regression and Random Forest Algorithm by Manisankar Sannigrahi, R. Thandeeswaran

“…Bayesian optimization is employed to systematically fine-tune the model’s hyperparameters, thereby improving accuracy and efficiency by concentrating on promising areas of the hyperparameter space and avoiding unnecessary evaluations. …”
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Optimal Design of Linear Quadratic Regulator for Vehicle Suspension System Based on Bacterial Memetic Algorithm by Bala Abdullahi Magaji, Aminu Babangida, Abdullahi Bala Kunya, Péter Tamás Szemes

“…The results of the LQR-BMA are compared with those of the optimized LQR based on the genetic algorithm (LQR-GA) and the Virus Evolutionary Genetic Algorithm (LQR-VEGA) to substantiate the potency of the proposed model. …”
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A Fast Fault Location Based on a New Proposed Modern Metaheuristic Optimization Algorithm by Mohammad Parpaei, Hossein Askarian-Abyaneh, Farzad Razavi

“…Moreover, a fast and accurate modern metaheuristic optimization algorithm for this cost function is proposed, which are key parameters to estimate the fault location methods based on optimization algorithms. …”
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Long-distance target localization optimization algorithm based on single robot moving path planning by Yourong Chen, Ke Wu, Yidan Guo, Kehua Zhao, Liyuan Liu

“…This approach solves the optimization model and obtains the optimal target positions and path trajectories, thereby improving the positioning accuracy for long-distance targets. …”
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Optimal Scheduling of Hydro-photovoltaic Complementary Systems Based on Multi-objective Moth-flame Algorithm by LI Ze-hong, YUAN Xiao-feng, XIAO Peng, ZHANG Tai-heng, QIN Hui

“…The combination of these two led to the development of a new high-performance multi-objective evolutionary algorithm: R-IMOMFO. A multi-objective optimization scheduling model for hydro-photovoltaic complementary systems was established, considering both power generation benefits and capacity benefits, and the model was solved using the R-IMOMFO algorithm. …”
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Optimal Design for an Extruder Head Runner Based on Response Surface Method and Simulated Annealing Algorithm by Haichao Zhou, Zhen Jiang, Wenchao Li, Guolin Wang, Yongjie Tu

“…The response surface model was optimized using the simulated annealing (SA) algorithm, and the optimal key factors of the head runner were obtained. …”
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Tabu Genetic Cat Swarm Algorithm Analysis of Optimization Arrangement on Mistuned Blades Based on CUDA by Yi Cai, Junjie Gu, Honggang Pan, Hongyuan Zhang, Tianyu Zhao

“…Tabu genetic cat swarm optimization algorithm is proposed for optimization arrangement on mistuned blades. …”
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OPTIMIZED CLUSTER-BASED COMMUNICATION IN MWSN USING FUZZY NEURAL NETWORKS AND CROW SEARCH ALGORITHM by S Archana, V Jayapradha

“…The CSA algorithm is used to guide cluster formation and CH selection by modeling the intelligent behavior of crows, resulting in energy-efficient partitioning of the network. …”
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Improved empirical wavelet transform combined with particle swarm optimization-support vector machine for EEG-based depression recognition by Yongxin Wang, Longqi Xu, Hongxu Qian, Haijun Lin, Xuhui Zhang

“…Therefore, there is a pressing need to develop techniques for detecting early signs of depression to enable timely intervention and potentially improve recovery rates. In this paper, we propose an improved method for the early objective diagnosis of depression utilizing an empirical wavelet transform (EWT) technique enhanced by a particle swarm optimization-support vector machine (PSO-SVM) algorithm. …”
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A Study on Container Storage Optimization in Yards Based on a Hyper-Heuristic Algorithm with a Q-Learning Mechanism by Lifen Chen, Jiajun Lin, Shihao Xu

“…The objective is to minimize the carbon emissions and the number of container rehandling operations in ports, for which a mixed-integer linear programming model is built. Both heuristic algorithms and hyper-heuristic algorithms are employed to optimize the container storage plan, and their applicability in storage optimization is compared. …”
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Self-optimization of Wind Turbine Variable-pitch Control Parameters Based on Adaptive Genetic Algorithm by CHANG Sheng, WAN Yubin, JIANG Tao

“…The author first described the basic principle of variable-pitch control system; then based on the genetic algorithm, planned and designed constraint conditions for different wind turbine models, covering initial population selection, self-optimization algorithm constraints and adaptability function design; and finally compared and analyzed the response curve, simulation and field operation results of the traditional parameter tuning method and self-optimization parameter tuning method. …”
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Sentiment analysis using long short term memory and amended dwarf mongoose optimization algorithm by Haisheng Deng, Ahmed Alkhayyat

“…To enhance the performance long short-term memory (LSTM), the model was optimized using the amended dwarf mongoose optimization (ADMO) algorithm, leading to improvements in the hyperparameters. …”
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A Multi-Surrogate Assisted Multi-Tasking Optimization Algorithm for High-Dimensional Expensive Problems by Hongyu Li, Lei Chen, Jian Zhang, Muxi Li

“…Surrogate-assisted evolutionary algorithms (SAEAs) are widely used in the field of high-dimensional expensive optimization. …”
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DGA-ACO: Enhanced Dynamic Genetic Algorithm—Ant Colony Optimization Path Planning for Agribots by Zhenpeng Zhang, Pengyu Li, Shanglei Chai, Yukang Cui, Yibin Tian

“…To overcome these challenges, this study proposes an enhanced Dynamic Genetic Algorithm—Ant Colony Optimization (DGA-ACO) framework. …”
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Optimizing Feature Selection and Machine Learning Algorithms for Early Detection of Prediabetes Risk: Comparative Study by Mahmoud B Almadhoun, MA Burhanuddin

“…ConclusionsIt is demonstrated in this research that optimized ML models, especially random forest and XGBoost, are effective tools for assessing early prediabetes risk. …”
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