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  1. 1321

    Estimation of elbow flexion torque using equilibrium optimizer on feature selection of NMES MMG signals and hyperparameter tuning of random forest regression by Raphael Uwamahoro, Raphael Uwamahoro, Kenneth Sundaraj, Farah Shahnaz Feroz

    Published 2025-02-01
    “…The performance of the GLEO-coupled with the RFR model was compared with the standard Equilibrium Optimizer (EO) and other state-of-the-art algorithms in physical and physiological function estimation using biological signals.ResultsExperimental results showed that selected features and tuned hyperparameters demonstrated a significant improvement in root mean square error (RMSE), coefficient of determination (R2) and slope with values improving from 0.1330 to 0.1174, 0.7228 to 0.7853 and 0.6946 to 0.7414, respectively for the test dataset. …”
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  2. 1322

    Bilevel Optimization Framework for Multiregional Integrated Energy Systems Considering 6G Network Slicing and Battery Energy Storage Capacity Sharing by Kun Cui, Ming Chi, Yong Zhao, Zhi-Wei Liu

    Published 2025-01-01
    “…The proposed line search-based global Levenberg–Marquardt algorithm addresses the limitations of existing algorithms with necessary and innovative improvements to tackle the challenge of global convergence in nonsmooth optimization problems. …”
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  3. 1323
  4. 1324

    Simultaneous OPEX and carbon footprint reduction with hydrogen enhancement in autothermal reforming: a machine learning–based surrogate modeling and optimization framework by Sahar Shahriari, Davood Iranshahi

    Published 2025-09-01
    “…The resulting solutions demonstrate notable improvements across all targeted criteria. The proposed framework helped reduce the simulation cost and also achieved 65.69 % higher hypervolume and 66.26 % lower IGD than the genetic algorithm. …”
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  5. 1325

    Optimization of sizing and energy management in hybrid energy storage systems for transient suppression in ship power systems under adverse sea conditions by Yu Ding, Shengping Ma, Guozheng Liu, Congbiao Sui, La Xiang

    Published 2025-09-01
    “…Moreover, compared to traditional optimization methods, the investment cost and installation space for the proposed IPS with optimal HESS are reduced by 53.9% and 54.2% respectively.…”
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  6. 1326

    Enhanced AUV Autonomy Through Fused Energy-Optimized Path Planning and Deep Reinforcement Learning for Integrated Navigation and Dynamic Obstacle Detection by Kaijie Zhang, Yuchen Ye, Kaihao Chen, Zao Li, Kangshun Li

    Published 2025-06-01
    “…This paper introduces a novel hybrid framework that synergistically fuses a Multithreaded Energy-Optimized Batch Informed Trees (MEO-BIT*) algorithm with Deep Q-Networks (DQN) to achieve robust AUV autonomy. …”
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  7. 1327
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    A source-load collaborative stochastic optimization method considering the electricity price uncertainty and industrial load peak regulation compensation benefit by Xiaoyu Yue, Lijun Fu, Siyang Liao, Jian Xu, Deping Ke, Huiji Wang, Shuaishuai Feng, Jiaquan Yang, Xuehao He

    Published 2025-06-01
    “…This paper combines the complete ensemble empirical mode decomposition adaptive noise (CEEMDAN), whale optimization algorithm (WOA), and long short-term memory network (LSTM) to propose a CEEMDAN-WOA-LSTM prediction model for electricity price scenarios. …”
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  9. 1329

    A Capacity Optimization Configuration Method for Photovoltaic and Energy Storage System of 5 G Base Station Considering Time-of-Use Electricity Price by Ziyan HAN, Shouxiang WANG, Qianyu ZHAO, Zhijie ZHENG

    Published 2022-09-01
    “…Then, the quantum-behaved particle swarm optimization algorithm is used to calculate the minimum comprehensive cost of the photovoltaic and energy storage system of 5G base station in a typical day to determine the optimal capacity of photovoltaic power generation and energy storage. …”
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  10. 1330

    The Robust Steiner Team Orienteering Problem with Decreasing Priorities under budgeted uncertainty by Lucas Assunção, Andréa Cynthia Santos

    Published 2025-12-01
    “…Post-disaster relief operations have gained attention over the past decade, focusing on enhancing resilience in labor and social environments. …”
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  11. 1331
  12. 1332

    Design of an intelligent AI-based multi-layer optimization framework for grid-tied solar PV-fuel cell hybrid energy systems by Prashant Nene, Dolly Thankachan

    Published 2025-12-01
    “…The results validate its capability when compared against traditional methods such as Genetic Algorithms and Particle Swarm Optimization. With this, we now have a scalable and real-time energy-efficient solution for future smart grid systems. • Integrated Intelligence Stack: Combines RL-ENN, T-STFREP, FL-DEO, GNNHSCO, and Q-GAN-ESO into a unified architecture for real-time control, forecasting, decentralized optimization, network routing, and synthetic scenario generation. • Real-Time, Scalable, and Privacy-Preserving: Enables adaptive energy dispatch, federated optimization without compromising data privacy, and graph-based power routing, making it suitable for large-scale, smart grid deployments. • Proven Long-Term Performance: Achieved significant improvements over traditional methods (GA, PSO) with 27.5 % lower NPC, 18.2 % reduction in COE, and 30.2 % increase in battery life, validated using 30 years of meteorological data.…”
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  13. 1333

    Synergistic Integration of LQR Control and PSO Optimization for Advanced Active Suspension Systems Utilizing Electro-Hydraulic Actuators and Electro-Servo Valves by Trong Tu

    Published 2025-06-01
    “…This research remarks the fundamentals of the experimental validation and further refinement of these control algorithms to adapt to various driving conditions and vehicle models, ultimately aiming to transition these optimized controllers from theoretical frameworks to practical, real-world applications. …”
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  14. 1334

    Integrating artificial Intelligence-Based metaheuristic optimization with Machine learning to enhance Nanomaterial-Containing latent heat thermal energy storage systems by Ali Basem, Hanaa Kadhim Abdulaali, As’ad Alizadeh, Pradeep Kumar Singh, Komal Parashar, Ali E. Anqi, Husam Rajab, Pancham Cajla, H. Maleki

    Published 2025-01-01
    “…The proposed strategy combines machine learning algorithms, including multilayer perceptron neural network (MLPNN), generalized additive model (GAM), Gaussian kernel regression (GKR), support vector machine (SVM), and Gaussian process regression (GPR) with artificial intelligence-based metaheuristic optimization algorithms (PSO and GA) to optimize their structural/training parameters. …”
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  15. 1335

    Explainable AutoML models for predicting the strength of high-performance concrete using Optuna, SHAP and ensemble learning by Muhammad Salman Khan, Tianbo Peng, Tianbo Peng, Muhammad Adeel Khan, Asad Khan, Mahmood Ahmad, Mahmood Ahmad, Kamran Aziz, Mohanad Muayad Sabri Sabri, N. S. Abd EL-Gawaad

    Published 2025-01-01
    “…Compared to a baseline model from the literature, O-LGB achieved significant improvements in predictive performance. For compressive strength, it reduced the Mean Absolute Error (MAE) by 87.69% and the Root Mean Squared Error (RMSE) by 71.93%. …”
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  16. 1336

    Spatial Downscaling of TRMM Precipitation Data Using an Optimal Subset Regression Model with NDVI and Terrain Factors in the Yarlung Zangbo River Basin, China by Jinping Liu, Wanchang Zhang, Ning Nie

    Published 2018-01-01
    “…After downscaling, the bias between TRMM 3B43 and rain gauge data decreased considerably from 0.397 to 0.109, the root-mean-square error decreased from 235.16 to 124.60 mm, and the r2 increased from 0.54 to 0.61, indicating significant improvement in the spatial resolution and accuracy of the TRMM 3B43 data. …”
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  17. 1337

    Spectrum Allocation Using Integer Linear Programming and Kerr Optical Frequency Combs by Sergio Muñoz-Tapasco, Andrés F. Calvo-Salcedo, Jose A. Jaramillo-Villegas

    Published 2024-11-01
    “…Spectrum allocation methods, such as the Routing, Modulation Level, and Spectrum Assignment (RMLSA) approach, play a crucial role in executing this strategy efficiently. While current algorithms have improved allocation efficiency, further development is necessary to optimize network performance. …”
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