Concrete Dam Deformation Prediction Model Based on Attention Mechanism and Deep Learning by ZHANG Hongrui, CAO Xin, JIANG Chao, ZU Anjun, XU Mingxiang

“…To address the multi-factor coupling, temporal dependency, and nonlinear complexity characteristics of concrete dam deformation, this paper proposed a hybrid prediction model integrating attention mechanisms, bidirectional long short-term memory (BiLSTM) networks, and sparrow search algorithm (SSA). The model comprehensively matched the multiple requirements of information weighting, temporal dependency modeling, and model optimization in concrete dam deformation prediction, forming a synergistic enhancement effect among methods.The attention mechanism operates on both feature and temporal dimensions to comprehensively enhance the model's focus on critical information. …”
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Evolved Motor Design Process to Reduce the Design Expense of Axial Flux Permanent Magnet Motor by Jong-Min Ahn, Dong-Kuk Lim, Min-Mo Koo

“…This paper proposes a design process that combines an initial electromagnetic design using analytical techniques with an optimal design based on a multi-objective optimization algorithm, aiming to reduce the design cost of an axial flux permanent magnet motor for urban air mobility traction. …”
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A Hybrid Evolutionary Fuzzy Ensemble Approach for Accurate Software Defect Prediction by Raghunath Dey, Jayashree Piri, Biswaranjan Acharya, Pragyan Paramita Das, Vassilis C. Gerogiannis, Andreas Kanavos

“…To address this, effective feature selection is essential but remains an NP-hard challenge best tackled with heuristic algorithms. This study introduces a binary, multi-objective starfish optimizer for optimal feature selection, balancing feature reduction and classification performance. …”
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Stochastic Planning of Synergetic Conventional Vehicle and UAV Delivery Operations by Konstantinos Kouretas, Konstantinos Kepaptsoglou

“…Then, a robust optimization approach is employed to propose the best solution that will perform well in a stochastic environment. …”
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Possibilities of magnet-resonance tomography usage while examining patients with reccurent genital prolapse by Banakhevych R.M.

“…Complex problem of establishing a diagnosis and choosing optimal treatment for patients with recurrent genital prolapse calls for improving preoperative clinical examination of these patients. …”
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A Practical Approach for Optimal Power Distribution Among the West-to-East Power Transmission Channels with Minimized Losses by Gaihong CHENG, Qingchun ZHU, Jing YAN

“…Based on the line search strategy including advance and retreat algorithm and golden section algorithm, the optimal power distribution among transmission channels is thus determined through a small number of iterations. …”
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Maximum power point tracking of photovoltaic module based on Particle Swarm Optimization enhanced with Quasi-Newton method. by Montaser Abdelsattar, Hamdi Ali Mohamed, Mohamed A Ismeil, Ahmed A Zaki Diab

“…The Particle Swarm Optimization (PSO) algorithm represents a powerful optimal MPP tracker due to its simplicity and has enhanced greatest exploration characteristics. …”
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Optimal fusion β-quaternion filtering from delayed observations and packet losses with compensation strategy under properness by J. D. Jiménez-López, R. M. Fernández-Alcalá, F. Gutiérrez-Trujillo, E. Grassucci, D. Comminiello

“…Under first-order properness conditions, a recursive algorithm is developed to compute the optimal filter. …”
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Optimal diagnostic strategy for coronavirus disease 2019 detection in liver transplant recipients: Critical review of available evidence by Michael T Olson, Tania Triantafyllou, Saurabh Singhal

“…Given the concerns for false-negative results, we performed a narrative review in effort to compile evidence for and against an optimal diagnostic algorithm for detecting COVID-19 in liver transplant recipients. …”
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Research on Capacity Optimization Configuration of Wind-solar-storage-load Micro-grid System Based on Energy Router by ZHANG Jietian, LI Chi

“…Based on the above micro-grid system model, the optimal energy storage configuration of wind power system and solar power system and system is realized by simulated annealing algorithm, and the accuracy and effectiveness of the proposed are verified by a case study. …”
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Robust Design Optimization of Viscoelastic Damped Composite Structures Integrating Model Order Reduction and Generalized Stochastic Collocation by Tianyu Wang, Chao Xu, Teng Li

“…Pareto optimal solutions are determined by combining the proposed MOR and gSC approaches with a well-established Non-dominated Sorting Genetic Algorithm II (NSGA-II) algorithm, which accounts for robustness in handling design variables, objectives, and constraints. …”
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Convergence Study of Minimizing the Nonconvex Total Delay Using the Lane-Based Optimization Method for Signal-Controlled Junctions by C. K. Wong, Y. Y. Lee

“…A set of constraints is set up to ensure the feasibility and safety of the resultant optimized lane markings and signal settings. The main difficulty to solve this high-dimension nonlinear nonconvex delay minimization problem using cutting plane algorithm is the requirement of substantial computational efforts to reach a good-quality solution while approximating the nonlinear solution space. …”
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Optimizing drone-based pollination method by using efficient target detection and path planning for complex durian orchards by Ruipeng Tang, Jianxun Tang, Mohamad Sofian Abu Talip, Narendra Kumar Aridas, Binghong Guan

“…This study proposes an AI-powered drone-based pollination method for complex durian orchards, integrating improved object detection and optimized path planning. Specifically, we enhance the YOLO-v8 algorithm using the GhostNet lightweight network to reduce computational complexity while boosting detection precision. …”
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A Bio-Optimization Approach for Renewable Energy Management: The Case of a University Building in a Tropical Climate by Orlando Aguilar Pinzón, Orlando Aguilar Gallardo, Miguel Chen Austin

“…These findings highlight some of the challenges with integrating renewable energy systems into existing buildings while showcasing the potential of biomimetic algorithms, like the PSO and the GA, for targeted optimization tasks. …”
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Streamlined Model Predictive Control for a Triple-Optimization of Thermal Comfort, Heating Costs, and Photovoltaic Self-Consumption by Vukasin Klepic, Magdalena Wolf, Tobias Proll

“…Building on existing low-tech MPC developments, this study extends them to enhance PV self-consumption optimization. The proposed streamlined MPC algorithm relies solely on weather forecast data and real-time electricity market prices to determine the required heating power input. …”
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Mixed fleet-based two-echelon vehicle routing optimization for cold chain logistics with diverse recharging strategies. by Yaling Li, Wenzhu Liao, Yuqi Huang

“…The presented model optimizes economic and environmental considerations to mitigate air pollution and reduce dependence on non-renewable energy sources while providing feasible routes. …”
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Robust techno-economic optimization of energy hubs under uncertainty using active learning with artificial neural networks by Aya M. A. Heikal, Shady H. E. Abdel Aleem, Ragab A. El-Sehiemy, Almoataz Y. Abdelaziz

“…The optimization approach under uncertainty provides robust predictive abilities across various scenarios, allowing the system to optimize energy management effectively, enhancing operational efficiency while minimizing overall energy losses, costs, and emissions. …”
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Optimization of Decision Support Technology for Offshore Oil Condition Monitoring with Carbon Neutrality as the Goal in the Enterprise Development Process. by Shiya Gao, Xin Guan, Xiaojing Cao, Zhili Bai, Caimeng Wang, Yun Zhan, Haiyang Yu

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Integrated Carbon Flow Tracing and Topology Reconfiguration for Low-Carbon Optimal Dispatch in DG-Embedded Distribution Networks by Rao Fu, Guofeng Xia, Sining Hu, Yuhao Zhang, Handaoyuan Li, Jiachuan Shi

“…To efficiently solve this complex constrained model, a novel Q-learning enhanced Moth Flame Optimization (QMFO) algorithm was proposed. QMFO synergized the global search capability of the Moth Flame Optimization (MFO) algorithm with the adaptive decision-making of Q-learning, embedding an adaptive exploration strategy to significantly enhance solution efficiency and accuracy for multi-objective problems. …”
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A Deep Reinforcement Learning-Based Speed Optimization System to Reduce Fuel Consumption and Emissions for Smart Cities by Yıldıray Yiğit, Murat Karabatak

“…This method provides safer, more comfortable travel while lowering emissions and fuel consumption. Simulations with various scenarios prove the Deep Q-Network (DQN) algorithm’s success in adjusting speed according to traffic lights. …”
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