Combination of Evolutionary Algorithms and Direct Search Approaches for Improving the Dynamic Performance of Grid Connected Solar Power System by Amit Verma, Prabhakar Tiwari, Desh Deepak Sharma

“…The study aimed to adjust the gains of the PI controllers in both static and dynamic irradiance scenarios for improving DC-link voltage by novel hybrid optimization method named Genetic Algorithm- Simulated Annealing and Genetic Algorithm- Pattern search. …”
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Design and optimization of a compact dual band metal insulator metal filter for high sensitivity refractive index sensing using particle swarm optimization by Ali Darabi, Mazdak Rad Malekshahi

“…The filter’s dimensions are optimized using the Particle Swarm Optimization (PSO) algorithm, ensuring maximum sensitivity and miniaturization. …”
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The impact of intravenous iodinated contrast agents on radiotherapy dose calculation and radiobiological effect predictions in central lung cancer by Defu Yang, Feng Shang, Ying Xu, Ying Yan

“…BackgroundAccurate dose calculation algorithms are critical for optimizing radiotherapy outcomes. …”
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Benchmarking a Novel Particle Swarm Optimization Dynamic Model Versus HOMER in Optimally Sizing Grid-Integrated Hybrid PV–Hydrogen Energy Systems by Ayatte I. Atteya, Dallia Ali

“…In this paper, a novel Particle Swarm Optimization (PSO) dynamic system model is developed by integrating a PSO algorithm with a precise dynamic hybrid PV-H₂ energy system model that is developed to accurately simulate the hybrid system by considering the dynamic behaviour of its individual system components. …”
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Optimizing Urban Air Mobility: A Ground-Connected Approach to Select Optimal eVTOL Takeoff and Landing Sites for Short-Distance Intercity Travel by Yantao Wang, Jiashuai Li, Yujie Yuan, Chun Sing Lai

“…Employing an enhanced iteration of the <italic>K</italic>-means algorithm, this phase undertakes the clustering of optimal takeoff and landing locations, thereby discerning their spatial distribution to effectively alleviate ground traffic congestion while aligning with eVTOL vertical port requirements and airspace regulatory mandates. …”
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Efficient Pathfinding on Grid Maps: Comparative Analysis of Classical Algorithms and Incremental Line Search by Amr Elshahed, Majid Khan Bin Majahar Ali, Ahmad Sufril Azlan Mohamed, Farah Aini Binti Abdullah, Ts. Lee Jian Aun

“…Pathfinding on grid maps is a cornerstone problem in robotics, autonomous navigation, and game development. Classical algorithms such as A*, Dijkstra&#x2019;s, and Breadth-First Search (BFS) are known for their ability to guarantee optimal solutions, while others like Depth-First Search (DFS) and Greedy Best-First Search prioritize speed over optimality. …”
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Cellular-free RAN slicing resource allocation algorithm based on multi-timescale collaboration by XIA Weiwei, WANG Boye, XIA Yaxing, MIAO Weiwei, WANG Dayang, JING Dongsheng, YAN Feng, SHEN Lianfeng

“…To address the issue of ensuring user quality of service in resource allocation for 6G cell-free radio access network slicing under dynamic service variations, a resource allocation algorithm based on multi-timescale collaborative optimization was proposed. …”
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The data analysis of sports training by ID3 decision tree algorithm and deep learning by Kaigong Wang, Lei Wang, Jiduo Sun

“…Abstract In order to improve the accuracy and efficiency of sports training data analysis, this paper proposes an optimized analysis model by combining Iterative Dichotomiser 3 (ID3) decision tree algorithm and deep learning model. …”
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A dereverberation beamforming algorithm for noise source localization in anechoic and semi-reverberant environments by R. Singh, A. Mimani, R. Kumar

“…Additionally, the CLEAN-SC deconvolution applied to the DBF maps of the mixer-grinder significantly improved the source resolution. • DBF algorithm is presented based on CCM filtering using an optimized Hanning window to significantly improve the localization accuracy of noise sources within λ/20 uncertainty. • Trial-and-error method is used to determine the optimal Hanning window width, which depends on frequency, noise source and surroundings. • It was necessary to implement DBF even in an anechoic chamber to accurately localize noise sources generated by engineering applications.…”
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Hybrid Estimation of Distribution Algorithm for Solving Three-Stage Multiobjective Integrated Scheduling Problem by Chao Deng, Rong Hu, Bin Qian, Huai P. Jin

“…A variable neighborhood hybrid operation based on the speed scheduling set is designed in Local Search II to further improve the quality of the solution while balancing the optimization goals. Finally, simulations and comparisons show the efficiency of the proposed HEDA_VNS.…”
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Comparative Study of Algorithms for the Conversion From Surface Mesh Models to Volume Mesh Models by Youxi Wang, Qi Pang, Meng Li, Yang Liu

“…The Delaunay algorithm performed best in terms of efficiency and model size, while the Frontal algorithm had an advantage in model refinement. …”
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Predictive PID Control for Automated Guided Vehicles Using Genetic Algorithm and Machine Learning by Kinza Nazir, Yong-Woon Kim, Yung-Cheol Byun

“…Specifically, the GA-optimized true PID values achieved a mean error of 11.8402, while the SVR-predicted PID values had a mean error of 15.4438, with SVR attaining a recall of 86.55%. …”
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A clustering algorithm based on grids for core data and adjacency relationships for edge data by Honglei He

“…To address these issues, existing research primarily focuses on three directions: (1) optimizing the adaptive selection of grid parameters, which struggles to handle variations in cluster density; (2) improving grid division methods (e.g., multi-granularity or dynamic grids), which have limited effectiveness on complex-shaped data; and (3) integrating other clustering techniques, which enhances accuracy but increases algorithmic complexity. …”
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SAMFA: A Flame Segmentation Algorithm for Infrared and Visible Aerial Images in the Same Scene by Jianye Yuan, Min Yang, Haofei Wang, Xinwang Ding, Song Li, Wei Gong

“…Lastly, to reduce the training difficulty, a progressive strategy combining self-supervised and fully supervised learning is employed to optimize the entire model. We compared SAMFA with five state-of-the-art image segmentation algorithms on a labeled public dataset, and the experimental results demonstrate that SAMFA performs the best. …”
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Risk of AI Algorithmic Discrimination Embedded in Government Data Governance and Its Prevention and Control by PENG Lihui, ZHANG Qiong, LI Tianyi

“…To address this issue, this study proposed a series of targeted prevention and control measures, including clarifying the principle of algorithmic fairness, formulating industry norms and standards, improving the accountability mechanism and regulatory system, and optimizing the data collection and processing environment, so as to effectively curb the phenomenon of algorithmic discrimination while making full use of the advantages of AI technology, so that AI technology in government data governance can truly benefit the people, and promote social fairness and justice.…”
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A Comparison of Machine Learning Algorithms for Predicting Alzheimer’s Disease Using Neuropsychological Data by Zakaria Mokadem, Mohamed Djerioui, Bilal Attallah, Youcef Brik

“…Hyperparameter tuning was performed to optimize model performance. The results indicate that ensemble learning models, particularly Gradient Boosting (GB) and Random Forest (RF), exhibited superior accuracy compared to other algorithms. …”
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Big Data and AI Algorithms for Sustainable Development Goals: A Topic Modeling Analysis by Prema Nedungadi, Simi Surendran, Kai-Yu Tang, Raghu Raman

“…In energy, AI-driven solutions optimize forecasting, grid management, and renewable integration, while in industry, they bolster infrastructure resilience through innovations like predictive maintenance and automated quality control within Industry 4.0 frameworks. …”
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Stress management with HRV following AI, semantic ontology, genetic algorithm and tree explainer by Ayan Chatterjee, Michael A. Riegler, K. Ganesh, Pål Halvorsen

“…Various techniques like feature selection and dimensionality reduction are explored to improve classification accuracy while minimizing bias. Different machine learning (ML) algorithms, including traditional and ensemble methods, are employed for analyzing both imbalanced and balanced HRV datasets. …”
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Mobile-YOLO: A Lightweight Object Detection Algorithm for Four Categories of Aquatic Organisms by Hanyu Jiang, Jing Zhao, Fuyu Ma, Yan Yang, Ruiwen Yi

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Construction and Application of Carbon Emissions Estimation Model for China Based on Gradient Boosting Algorithm by Dongjie Guan, Yitong Shi, Lilei Zhou, Xusen Zhu, Demei Zhao, Guochuan Peng, Xiujuan He

“…Key variables were selected through correlation analysis, missing values were interpolated using K-means clustering, and model parameters were systematically optimized via grid search and cross-validation. Among the algorithms tested, LightGBM achieved the best performance (R² = 0.992, RMSE = 0.297), demonstrating both robustness and efficiency. …”
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