Multiperiod Location–Allocation Optimization of Construction Logistics Centers for Large-Scale Projects in Complex Environmental Regions by Hao Shen, Jin Zhang, Wenjie Sun, Wenguang Yang, Guoqi Li

“…We have designed an NSGA-II based on endocrine hormone regulation (EHR-NSGA-II) to solve the model. Finally, a large-scale railroad construction project in complex environmental regions is used as an example to prove the effectiveness of the model and algorithm. …”
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Design of intelligent optimization of sports strategy and training decision support system based on deep reinforcement learning by Hua Xu, Bing Lin, Long Liu

“…The data is preprocessed by a sliding window average filter algorithm to eliminate noise and outliers. The system adopts the DQN (Deep Q-Network) architecture and applies dual DQN technology to improve model stability. …”
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Optimal State Estimation in Underwater Vehicle Discrete-Continuous Measurements via Augmented Hybrid Kalman Filter by Vadim Kramar, Kirill Dementiev, Aleksey Kabanov

“…State-vector augmentation is proposed to improve the estimation convergence. The authors present numerical modeling results demonstrating the algorithm’s efficiency on the example of motion parameter estimation for the autonomous underwater vehicle. …”
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Online Estimation and Control Method of Optimal Slip Ratio for Vehicle With an Electric Power-Assisted Brake System by Lei Chen, Yuchao He, Tangtang Ma, Shengshi Zhong

“…Current algorithms for estimating the optimal slip ratio is still room for improving the accuracy and efficiency, especially under the changing road surface, introducing significant lag. …”
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Coordinated Scheduling of Distribution Networks and Microgrids Considering Heat Pump Load and Distributed Photovoltaic by Shihui LI, Qi WANG, Xiaobo JIA, Wenchuan WU, Huayang LIANG, Lin ZHU

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Enhancing shear strength predictions of UHPC beams through hybrid machine learning approaches by Sanjog Chhetri Sapkota, Ajad Shrestha, Moinul Haq, Satish Paudel, Waiching Tang, Hesam Kamyab, Daniele Rocchio

“…This study proposes hybrid ML models that integrate three nature inspired metaheuristic algorithms—Giant Armadillo Optimization (GOA), Spotted Hyena Optimization (SHO) and Leopard seal optimization (LSA)- Extreme Gradient Boosting (XGB) to predict the shear strength of UHPC beams. …”
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A quasi affine transformation evolution algorithm with evolution matrix selection operation for parameter estimation of proton exchange membrane fuel cells by Mohammad Aljaidi, Pradeep Jangir, Sunilkumar P. Agrawal, Sundaram B. Pandya, Anil Parmar, Samar Hussni Anbarkhan, Laith Abualigah

“…It is challenging to find the best PEMFC parameters because the model is complex and the problem is nonlinear; not all optimization algorithms can solve this problem. …”
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Enhancing CO2 emissions prediction for electric vehicles using Greylag Goose Optimization and machine learning by Ahmed El-Sayed Saqr, Mohamed S. Saraya, El-Sayed M. El-Kenawy

“…Finally, the study does a comparative analysis with some established optimization algorithms in hyperparameter tuning regarding an improved accuracy model. …”
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A Modified Pareto Ant Colony Optimization Approach to Solve Biobjective Weapon-Target Assignment Problem by You Li, Yingxin Kou, Zhanwu Li, An Xu, Yizhe Chang

“…Simulation results show that the proposed algorithm is successfully applied in the field of WTA which improves the performance of the traditional P-ACO algorithm effectively and produces better solutions than the two well-known multiobjective optimization algorithms NSGA-II and SPEA-II.…”
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Improved Iterative CD-Spline Approach for Building Boundary Regularization Using Airborne LiDAR Data by Renato Cesar dos Santos, Ayman F. Habib, Mauricio Galo

“…To overcome this limitation, we proposed the Improved Iterative Changeable Degree-Spline (IICDS) that consists of testing several CP configurations, resulting in multiple contour models for each building. …”
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Suicide Risk Screening in Jails: Protocol for a Pilot Study Leveraging the Mental Health Research Network Algorithm and Health Care Data by Erin B Comartin, Grant Victor, Athena Kheibari, Brian K Ahmedani, Bethany Hedden-Clayton, Richard N Jones, Ted R Miller, Jennifer E Johnson, Lauren M Weinstock, Sheryl Kubiak

“…This study will use administrative data and ML modeling to improve suicide risk detection at jail booking. …”
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Diversifying Multi-Head Attention in the Transformer Model by Nicholas Ampazis, Flora Sakketou

“…The diversification of the heads is achieved through a single-layer feed-forward neural network that is added to the Transformer architecture and is trained with the proposed algorithm. We utilize the algorithm in three different architectural variations of the baseline Transformer model. …”
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Carbon Emission Reduction in Traffic Control: A Signal Timing Optimization Method Based on Rainbow DQN by Juan Lv, Zhaowei Wang, Jianxiao Ma

“…To improve intersection traffic flow and reduce vehicle energy consumption and emissions at intersections, a signal optimization method based on deep reinforcement learning (DRL) is proposed. …”
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Double-layer stacking optimization for electricity theft detection considering data incompleteness and intra-class imbalance by Leijiao Ge, Jingjing Li, Tianshuo Du, Luyang Hou

“…This enables balanced synthesis of theft samples using these patterns as conditional supervisory terms for TimeGAN. To concurrently optimize the combination of the electricity theft detector (ETD) model and its hyperparameters, an integrated two-layer Stacking optimization framework is developed. …”
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RE-YOLOv5: Enhancing Occluded Road Object Detection via Visual Receptive Field Improvements by Tianyu Li, Xuanrui Xiong, Yuan Zhang, Xiaolin Fan, Yushu Zhang, Haihong Huang, Dan Hu, Mengting He, Zhanjun Liu

“…The proposed method achieves a mean average precision (mAP) of 82.04% on KITTI, representing an improvement of 2.34% over the baseline model. For heavily occluded objects on CityPersons, the Log Average Miss Rate (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mi>MR</mi><mrow><mo>−</mo><mn>2</mn></mrow></msup></semantics></math></inline-formula>) is reduced to 40.31%, which is a decrease of 9.65% compared to the baseline. …”
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Design and Analysis of an Interior Permanent Magnet Synchronous Motor for a Traction Drive Using Multiobjective Optimization by Yingying Xu, Yiguang Chen, Zhihua Fu, Mingxia Xu, Haiyu Liu, Li Cheng

“…Based on the genetic algorithm, a multiobjective optimization mechanism of the magnetic pole structure is established. …”
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A TD3-Based Reinforcement Learning Algorithm With Curriculum Learning for Adaptive Yaw Control in All-Wheel-Drive Electric Vehicles by Reza Jafari, Pouria Sarhadi, Amin Paykani, Shady S. Refaat, Pedram Asef

“…The proposed model-free torque vectoring algorithm performs based on the interaction of an agent with an environment to learn the optimal policy in a reward-driven manner and obtain the ability to dynamically adapt to varying conditions, such as different roads and vehicle speeds. …”
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Metaheuristic Optimization of Fractional Order Incremental Conductance (FO-INC) Maximum Power Point Tracking (MPPT) by Hossam Hassan Ammar, Ahmad Taher Azar, Raafat Shalaby, M. I. Mahmoud

“…This paper seeks to improve the photovoltaic (PV) system efficiency using metaheuristic, optimized fractional order incremental conductance (FO-INC) control. …”
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A multi-objective aerodynamic performance optimization of a centrifugal vacuum pump and the flow physics analysis by Zhanyuan Gu, Jiangtao Zhang, Wei Zhang, Yikun Wei

“…The backpropagation neural network was employed as the surrogate model, and the multi-objective optimization was performed using the non-dominated sorting genetic algorithm. …”
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Optimal Configuration of Additional Heat Source for CHP System considering Demand Response Based on Comprehensive Benefits by Yuting Zhao

“…Furthermore, an improved memetic algorithm (IMA) combined with a hierarchical sequence method is designed to solve the optimization model characterized by multiple objectives, hierarchical levels, and nonlinearity. …”
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