Smart Energy Strategy for AC Microgrids to Enhance Economic Performance in Grid-Connected and Standalone Operations: A Gray Wolf Optimizer Approach by Sebastian Lobos-Cornejo, Luis Fernando Grisales-Noreña, Fabio Andrade, Oscar Danilo Montoya, Daniel Sanin-Villa

“…To assess performance, 100 independent runs per method were conducted, comparing GWO against particle swarm optimization (PSO) and genetic algorithms (GAs). Statistical analysis confirmed that GWO achieved the lowest operational costs (USD 3299.39 in grid-connected mode and USD 11,367.76 in islanded mode), the highest solution stability (0.19% standard deviation), and superior voltage regulation. …”
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Optimizing deep belief network for concrete crack detection via a modified design of ideal gas molecular dynamics by Tan Qin, Gongxing Yan, Huaguo Jiang, Minqi Shen, Andrea Settanni

“…The present research concentrates on the development of crack diagnosis algorithms based on vision using an optimized version of Deep Neural Network (DNN). …”
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Enhancing agricultural sustainability: Optimizing crop planting structures and spatial layouts within the water-land-energy-economy-environment-food nexus by Haowei Wu, Zhihui Li, Xiangzheng Deng, Zhe Zhao

“…In this framework, the NSGA-II algorithm was used to construct the multi-objective optimization model of crop planting structures with consideration of water and energy consumption, greenhouse gas (GHG) emissions, economic benefits, as well as food, land, and water security constraints, while the model for planting spatial layout optimization was established with consideration of crop suitability using the MaxEnt model and the improved Hungarian algorithm. …”
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Symbiotic Learning Grey Wolf Optimizer for Engineering and Power Flow Optimization Problems by Aala Kalananda Vamsi Krishna Reddy, Komanapalli Venkata Lakshmi Narayana

“…This article presents a symbiotic learning-based Grey Wolf Optimizer (SL-GWO) formulated through the introduction of symbiotic hunting and learning strategies to achieve a better trade-off between exploration and exploitation while standing immune to the curse of dimensionality. …”
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PFW-YOLO Lightweight Helmet Detection Algorithm by Yue Hong, Hao Wang, Shuo Guo

“…The final experimental results indicate that, compared to the original YOLOv8n algorithm, the PFW-YOLO algorithm achieves a 53% reduction in parameters, a 42% decrease in computational effort, and a 51% reduction in model size, while enhancing the mean average precision (mAP) by 0.4%.…”
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A Dual-Strategy Framework for Cyber Threat Detection in Imbalanced, High-Dimensional Data Across Heterogeneous Networks by T. Saranya, S. Indra Priyadharshini

“…Second, the Cauchy-Gaussian Genetic-Arithmetic Optimizer (CG-GAO) addresses the challenge of high-dimensional data by combining a genetic algorithm (GA) and an arithmetic optimization algorithm (AOA), enhancing exploration and preventing premature convergence. …”
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Intelligent design of high-performance fluids for thermal management: integrating response surface methodology, weighted Tchebycheff method, and strength Pareto evolutionary algori... by Mohamed Bechir Ben Hamida, Ali Basem, Neeraj Varshney, Loghman Mostafa

“…This study presents a novel multi-objective optimization framework integrating response surface methodology (RSM) with enhanced hill climbing (EHC) algorithm and strength Pareto evolutionary algorithm II (SPEA-II) to optimize multiple TPPs. …”
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End-to-End Collaborative Optimization Method for Microgrid Power Prediction and Optimal Scheduling by ZHANG Li, WANG Bao, JIA Jianxiong, SONG Zhumeng, YE Yutong, YU Yue, LIN Jiaqing, XU Xiaoyuan

“…Initially, a bi-level optimization framework is established. The upper level focuses on training the power forecasting model, formulated as a combined forecasting problem, while the lower level aims to minimize microgrid operational costs. …”
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Optimal scheduling of distributed shared energy storage based on optimal SOC interval by Tong Zhang, Liudong Zhang, Yan Chen, Zhiqiang Peng

“…The paper delves into the scheduling techniques for SES. While conventional day-ahead robust optimization algorithms specify ESS power output for each period, they struggle to adjust schedules due to time-dependent constraints like renewable energy output and ESS state limitations. …”
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Generation Algorithms for Thévenin and Norton Equivalent Circuits by Mihaela Grib, Ioana-Gabriela Sirbu, Lucian Mandache, Marilena Stanculescu, Mihai Iordache, Lavinia Bobaru, Dragos Niculae

“…The growing complexity of electrical systems requires advanced analysis tools to optimize the design time and resources. While many circuit simulators exist, they often lack the flexibility needed for real-world applications. …”
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Self-adaptive multi-population quadratic approximation guided jaya optimization applied to economic load dispatch problems with or without valve-point effects by Sukriti Patty, Rajeev Das, Dharmadas Mandal, Provas Kumar Roy

“…This study applies the Self-Adaptive Multi-Population Quadratic Approximation Guided Jaya (SMP-JaQA) algorithm, a state-of-the-art parameter-free optimization technique, to solve the ELD problem effectively. …”
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Optimization of the prognosis of postoperative complications in patients with breast cancer by L. A. Trusova

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Multifactor Algorithm for Test Case Selection and Ordering by Atulya Gupta, Rajendra Prasad Mahapatra

“…Many former studies revealed the heuristic-dependent mechanism to attain optimality while reducing or prioritizing test cases. …”
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Subsampling Algorithms for Irregularly Spaced Autoregressive Models by Jiaqi Liu, Ziyang Wang, HaiYing Wang, Nalini Ravishanker

“…The effectiveness of these methods depends on their ability to identify and select data points that improve the estimation efficiency according to some optimality criteria. While much of the existing research has focused on subsampling techniques for independent data, there is considerable potential for developing methods tailored to dependent data, particularly in time-dependent contexts. …”
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Cooperative routing algorithm based on game theory by Kun XIE, Shen-lin DUAN, Ji-gang WEN, Shi-ming HE

“…The proposed repeated routing game can approach to pareto optimality. Simulation result shows that this algorithm is capable of promoting cooperation between selfish nodes, which results in high delivery ratio, low transmission delay and energy consumption.…”
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Cooperative routing algorithm based on game theory by Kun XIE, Shen-lin DUAN, Ji-gang WEN, Shi-ming HE

“…The proposed repeated routing game can approach to pareto optimality. Simulation result shows that this algorithm is capable of promoting cooperation between selfish nodes, which results in high delivery ratio, low transmission delay and energy consumption.…”
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Exact Algorithms for the Satellite Image Selection Problem by Swat Sylwester, Antczak Maciej, Zok Tomasz, Blazewicz Jacek, Musial Jedrzej

“…The main question is how to optimally select the subset of available images to fully cover the AOI while minimizing total cost and cloud coverage. …”
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Stochastic Explicit Calibration Algorithm for Survival Models by Jeongho Park, Sangwook Kang, Gwangsu Kim

“…In this study, we introduce Stochastic Explicit Calibration (S-cal), an algorithm that employs random intervals instead of fixed bins, thereby advancing the calibration methods used in deep networks. …”
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An Environment Recognition Algorithm for Staircase Climbing Robots by Yanjie Liu, Yanlong Wei, Chao Wang, Heng Wu

“…For deformed wheel-based staircase-climbing robots, the accuracy of staircase step geometry perception and scene mapping are critical factors in determining whether the robot can successfully ascend the stairs and continue its task. Currently, while there are LiDAR-based algorithms that focus either on step geometry detection or scene mapping, few comprehensive algorithms exist that address both step geometry perception and scene mapping for staircases. …”
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A New Approach Based on Metaheuristic Optimization Using Chaotic Functional Connectivity Matrices and Fractal Dimension Analysis for AI-Driven Detection of Orthodontic Growth and D... by Orhan Cicek, Yusuf Bahri Özçelik, Aytaç Altan

“…Feature selection was performed using a wrapper-based approach combining k-nearest neighbors (kNN) and the Puma optimization algorithm, which efficiently handles the chaotic and computationally complex nature of cervical vertebrae images. …”
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