Efficient cooling capability in microchannel heat sink reinforced with Y-shaped fins: Based on artificial neural network, genetic algorithm, Pareto front, and numerical simulation by Xiang Ma, Ali Basem, Pradeep Kumar Singh, Rebwar Nasir Dara, Ahmad Almadhor, Amira K. Hajri, Raymond Ghandour, Barno Abdullaeva, H. Elhosiny Ali, Samah G. Babiker

“…A genetic algorithm was employed for single-objective optimization targeting three criteria: maximizing total efficiency, minimizing pressure drop, and maximizing the Nusselt number. …”
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Network Optimization of Fresh Products Cold Chain Considering Supply Disruption and Demand Fluctuation Under the Dual-Carbon Policy by Haojie Ran, Dichen He, Huajun Tang

“…The research results provide valuable decision-making support for fresh cold chain enterprises to develop resilient and low-carbon network optimization strategies for cost reduction, efficiency improvement, and sustainable development.…”
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Optimizing multi-objective hybrid energy systems with pumped hydro storage for enhanced stability and efficiency in renewable energy integration by Junxian Li, Jiaxin Yuan, Xuxin Yue

“…This efficient strategy consists of the inherent complexities, which is solved by the NSGA-II algorithm. The multi-objective approach of optimization procedure performs Pareto solution sets that reflects trade-offs between remaining load variations and operational costs. …”
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Adaptive Neuro-Fuzzy Inference System-Genetic Algorithm approach for global maximum power point tracking in PV systems under different shading conditions by Nivine Guler, Zied Ben Hazem, Ali Gunes, Firas Saidi

“…An inherent problem with most conventional global maximum power point tracking (GMPPT) algorithms is that they do not distinguish local and global peaks, and thus energy extraction may not be optimal. …”
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Influence of soil parameters on dynamic compaction: numerical analysis and predictive modeling using GA-optimized BP neural networks by Yu Zhang, Xueshui Chen, Huakang Ge, Zhigang Guo, Xu Li

“…Orthogonal experimental design and single factor analysis were used to quantify the influence of each parameter on the compaction volume. In order to improve the prediction accuracy, this paper introduces genetic algorithm (GA) to optimize the BP neural network model, constructs a multi-factor dynamic compaction prediction model, and compares it with the traditional BP model. …”
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Meta-RHDC: Meta Reinforcement Learning Driven Hybrid Lyrebird Falcon Optimization for Dynamic Load Balancing in Cloud Computing by Mallu Shiva Rama Krishna, D. Khasim Vali

“…By integrating reinforcement learning with advanced optimization techniques, Meta-RHDC significantly improves task scheduling and load balancing compared to existing methods such as Load Optimization Algorithm (LOA), Reinforcement Learning (RL), and Falcon Optimization Algorithm (FOA). …”
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Achieving local differential location privacy protection in 3D space via Hilbert encoding and optimized random response by Yan Yan, Pengbin Yan, Adnan Mahmood, Yang Zhang, Quan Z. Sheng

“…Experiments on the real spatial location datasets show that the suggested method can reduce spatial location service quality loss, maintain the availability of perturbed spatial location and improve the operation efficiency of the spatial location perturbation algorithm.…”
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Recurrent academic path recommendation model for engineering students using MBTI indicators and optimization enabled recurrent neural network by Anupama V, Sudheep Elayidom M

“…At last, an adaptive recommendation of the engineering department is performed using DRNN, which is trained based on the Magnetic Invasive Weed Optimization (MIWO) algorithm. On the other hand, MBTI personality type categorization is done, wherein the correlation of courses with MBTI outcome is detected using MIWO-based DRNN. …”
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Enhancing Streamflow Prediction Accuracy: A Comprehensive Analysis of Hybrid Neural Network Models with Runge–Kutta with Aquila Optimizer by Rana Muhammad Adnan, Wang Mo, Ahmed A. Ewees, Salim Heddam, Ozgur Kisi, Mohammad Zounemat-Kermani

“…Abstract This study investigates the efficacy of hybrid artificial neural network (ANN) methods, incorporating metaheuristic algorithms such as particle swarm optimization (PSO), genetic algorithm (GA), gray wolf optimizer (GWO), Aquila optimizer (AO), Runge–Kutta (RUN), and the novel ANN-based Runge–Kutta with Aquila optimizer (LSTM-RUNAO). …”
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Optimization of Electric Vehicle Charging and Discharging Strategies Considering Battery Health State: A Safe Reinforcement Learning Approach by Shuifu Gu, Kejun Qian, Yongbiao Yang

“…With the widespread adoption of electric vehicles (EVs), optimizing their charging and discharging strategies to improve energy efficiency and extend battery life has become a focal point of current research. …”
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Daily reference evapotranspiration prediction in Iran: A machine learning approach with ERA5-land data by Ali Asghar Zolfaghari, Maryam Raeesi, Giuseppe Longo-Minnolo, Simona Consoli, Miles Dyck

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Machine Learning Framework for Early Detection of Chronic Kidney Disease Stages Using Optimized Estimated Glomerular Filtration Rate by Samit Kumar Ghosh, Namareq Widatalla, Ahsan H. Khandoker

“…The application of GWO for hyperparameter tuning has resulted in a 37.3% reduction in root mean square error (RMSE), a 37.4% drop in mean absolute percentage error (MAPE), and a 2.06% improvement in <inline-formula> <tex-math notation="LaTeX">$\text {R}^{2}$ </tex-math></inline-formula> to improve the precision of prediction. …”
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Enhanced Disc Herniation Classification Using Grey Wolf Optimization Based on Hybrid Feature Extraction and Deep Learning Methods by Yasemin Sarı, Nesrin Aydın Atasoy

“…Following feature extraction, the GWO algorithm, inspired by the social hierarchy and hunting behavior of grey wolves, is employed to optimize the feature set by selecting the most relevant features. …”
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Toward a linear-ramp QAOA protocol: evidence of a scaling advantage in solving some combinatorial optimization problems by J. A. Montañez-Barrera, Kristel Michielsen

“…Abstract The quantum approximate optimization algorithm (QAOA) is a promising algorithm for solving combinatorial optimization problems (COPs), with performance governed by variational parameters $${\{{\gamma }_{i},{\beta }_{i}\}}_{i = 0}^{p-1}$$ { γ i , β i } i = 0 p − 1 . …”
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Enhancing grid connected wind energy conversion systems through fuzzy logic control optimization with PSO and GA techniques by Abdelhalim Borni, Noureddine Bessous, Layachi Zaghba, Abdelhak Bouchakour, Melkamu Sisay Agmas, Enas Ali, Sherif S. M. Ghoneim, Ayman Hoballah

“…Abstract This paper presents the design and simulation of an optimized fuzzy logic Maximum Power Point Tracking (MPPT) controller for grid-tied wind turbines, utilizing Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). …”
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Co-Optimization Operation of Distribution Network-Containing Shared Energy Storage Multi-Microgrids Based on Multi-Body Game by Hao Wu, Ge Cao, Rong Jia, Yan Liang

“…Finally, based on the power interaction of microgrids to measure their contributions, an improved Shapley value cost allocation method is proposed, effectively achieving a balanced distribution of benefits among the distribution network, shared energy storage, and multi-microgrids, thereby improving overall operational revenue. …”
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Virtual power plant to ensure reliable power supply and accident-free operation of process equipment of a mining enterprise by Telmanova E.D., Abdrakhmanov I.D.

“…The paper presents a schematic diagram and stages of building a mathematical model of BAS. Structural optimization of this algorithm, which improves the topology of the system, has been performed. …”
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Next generation network resource allocation method based on cooperative game and decision-making in advance by RAO Xiang, ZHANG Shun-yi, SUN Yan-fei, DING Wen-tao

“…It’s an important way to guarantee QoS for the next generation network（NGN） with diverse services by allo-cating resources reasonably and optimizing the efficiency of whole network according to diverse service styles.A net-work resource allocating method based on co-operative game theory for NGN was proposed and analyzed,and it had a weakness which brought about overgreat system costing.In order to overcome this weakness,an idea about deci-sion-making in advance was added,and an improved resource allocation algorithm was proposed,which could guarantee the efficiency of whole network best and reduce the system costing.Simulation results of this method show its validity.…”
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Medical Dataset Classification: A Machine Learning Paradigm Integrating Particle Swarm Optimization with Extreme Learning Machine Classifier by C. V. Subbulakshmi, S. N. Deepa

“…This paradigm integrates the successful exploration mechanism called self-regulated learning capability of the particle swarm optimization (PSO) algorithm with the extreme learning machine (ELM) classifier. …”
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Dimensional Accuracy Analysis of Splined Shafts and Hubs Obtained by Fused-Deposition Modeling 3D Printing Using a Genetic Algorithm and Artificial Neural Network by Alin-Daniel Rizea, Cristina-Florena Banică, Tatiana Georgescu, Alexandru Sover, Daniel-Constantin Anghel

“…Three-dimensional printing, especially FDM, enables fast production of customized components with complex geometries, reducing material waste and costs. Optimized printing parameters improve dimensional accuracy and performance. …”
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