Random forest algorithm integrated with an initial basic feasible solution in buckling analysis of a two-dimensional functionally graded porous taper beam by Ravikiran Chinthalapudi, Jagadesh Kumar Jatavallabhula, Geetha Narayanan Kannaiyan, Bridjesh Pappula, Seshibe Makgato

“…To overcome these limitations, a hybrid analytical computational methodology is proposed that integrates the novel Initial Basic Feasible Solution approach with the Random Forest algorithm. The beam is modelled using hyperbolic shear deformation theory to account for transverse shear effects, while material properties vary along both the length and thickness following a power-law distribution. …”
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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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Performance Optimization of a Formula Student Racing Car Using the IPG CarMaker, Part 1: Lap Time Convergence and Sensitivity Analysis by Dominik Takács, Ambrus Zelei

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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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Detecting soil mixing, grain size distribution, and clogging potential of tunnel excavation face by classification-regression algorithms using EPBM operational data by Sharmin Sarna, Marte Gutierrez

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A hybrid mutational Northern Goshawk and elite opposition learning artificial rabbits optimizer for PEMFC parameter estimation by Pradeep Jangir, Absalom E. Ezugwu, Kashif Saleem, Arpita, Sunilkumar P. Agrawal, Sundaram B. Pandya, Anil Parmar, G. Gulothungan, Laith Abualigah

“…Additionally SSE, Absolute Error (AE), and Mean Bias Error (MBE) are computed for different recent methods according to literature on voltage measurement. Other optimization algorithms including ARO, TLBO, DE and SSA are used for comparative analysis purposes. …”
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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

“…Liver transplant centers should validate the algorithm presented herein, which is based on existing evidence and designed to maximize patient and provider safety, while assuring accuracy in diagnosis.…”
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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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Architectural Exploration and Performance Enhancement of the CVA6 RISC-V Core Using the Gem5 Simulation Framework by Umer Shahid, Muhammad Tahir, Bilal Zafar, Ayesha Ahmad, Shanzay Wasim, Bisal Saeed

“…To further enhance the architecture, we integrated machine learning algorithms to optimize performance and resource efficiency. …”
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A novel approach for music genre identification using ZFNet, ELM, and modified electric eel foraging optimizer by Shuang Zhang, Zhiyong Sun, Hasan Jafari

“…Furthermore, the model incorporates a newly developed metaheuristic algorithm called the Modified Electric Eel Foraging Optimization (MEEFO) algorithm to optimize the ELM parameters and enhance overall performance. …”
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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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