AI-based routing algorithms improve energy efficiency, latency, and data reliability in wireless sensor networks by Rahul Priyadarshi, Ravi Ranjan Kumar, Rakesh Ranjan, Padarti Vijaya Kumar

“…Each AI module plays a distinct role-RL handles local routing decisions, while GA and PSO are invoked for global optimization under resource constraints. …”
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An effective feature selection approach based on hybrid Grey Wolf Optimizer and Genetic Algorithm for hyperspectral image by Yiqun Shang, Minrui Zheng, Jiayang Li, Xinqi Zheng

“…Abstract Feature selection (FS) is a critical step in hyperspectral image (HSI) classification, essential for reducing data dimensionality while preserving classification accuracy. However, FS for HSIs remains an NP-hard challenge, as existing swarm intelligence and evolutionary algorithms (SIEAs) often suffer from limited exploration capabilities or susceptibility to local optima, particularly in high-dimensional scenarios. …”
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Multiclass Sentiment Analysis of Electric Vehicle Incentive Policies Using IndoBERT and DeBERTa Algorithms by Muhammad Bayu Nugroho, Akhmad Khanif Zyen, Nur Aeni Widiastuti

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Time-varying MVAR algorithms for directed connectivity analysis: Critical comparison in simulations and benchmark EEG data. by Mattia F Pagnotta, Gijs Plomp

“…Here, we critically compare four recursive tvMVAR algorithms and assess their performance while systematically varying adaptation coefficients, model order, and signal sampling rate. …”
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Multi-objective: hybrid particle swarm optimization with firefly algorithm for feature selection with Leaky ReLU by Ashish Kumar Singh, Anoj Kumar

“…The reason behind selecting PSO is that it is well-suited for smaller search spaces, while the Firefly Algorithm (FA) excels in larger search spaces, making their hybridization particularly effective. …”
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A Hybrid Genetic Algorithm and Proximal Policy Optimization System for Efficient Multi-Agent Task Allocation by Zimo Zhu, Chuanqiang Yu, Junti Wang

“…These findings highlight the algorithm’s robustness and efficiency in handling large-scale and computationally intensive coordination tasks.…”
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An Improved 2D Pose Estimation Algorithm for Extracting Phenotypic Parameters of Tomato Plants in Complex Backgrounds by Yawen Cheng, Ni Ren, Anqi Hu, Lingli Zhou, Chao Qi, Shuo Zhang, Qian Wu

“…However, segmentation-based methods are labor-intensive due to their requirement for extensive annotation during training, while object detection approaches exhibit limitations in capturing intricate structural features. …”
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An improved fluid flow algorithm for hydraulic fracturing: Optimizing domain volume and crack pressure update strategies by Wei Zhang, Jing Bi, Yu Zhao, Yongfa Zhang, Chaolin Wang, Yang Pan

“…This paper proposes an improved fluid flow algorithm, aiming to enhance the computational efficiency of hydraulic fracturing simulations while ensuring computational accuracy. …”
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Q-LME: Q-learning-based local mutual exclusion algorithm for flying ad hoc networks by Sindhuja S, Mary Anita Rajam V

“…Q-LME employs a token-based LME algorithm with a Q-learning-based leader selection mechanism (QLS). …”
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Evaluation of Dose Calculation Algorithms Accuracy for ISOgray Treatment Planning System in Motorized Wedged Treatment Fields by Sajjad Raghavi, Hamid-Reza Sadoughi, Mohammad Ehsan Ravari, Marziyeh Behmadi

“…This discrepancy is attributed to the increased presence of scattered photons and the variation in the delivered dose within the wedge field, consequently impacts the beam quality. While the CCC and FFT algorithms had better accuracy, the Clarkson algorithm, particularly at larger effective wedge angles, exhibited greater effectiveness than the two mentioned algorithms.…”
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A Comparative Study of K-means Clustering Algorithms Using Euclidean and Manhattan Distance for Climate Data. by Bakhshan Hamad

“…WCSS values were similar, with Random and Canopy scoring lowest, but within Manhattan Distance, all algorithms again formed two clusters. Canopy had the highest iterations, Farthest First the fewest and fastest, while Random was slowest. …”
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AB-VIP: Attack Method Using Brightness Information for Visibility Improvement of Adversarial Perturbations on the NMS Algorithm by Gwang-Nam Kim, Han-Ju Lee, Han-Jin Lee, Hyeon-Jin Jung, Seok-Hwan Choi

“…In particular, adversarial attacks on key components of object detection models such as Region Proposal Network (RPN) and Non-Maximum Suppression (NMS) algorithms have recently been highlighted. As a representative adversarial attack method targeting the NMS algorithm, PhantomSponges disrupts the normal operation of the NMS algorithm by using universal perturbations. …”
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Lung Cancer Classification Using the Extreme Gradient Boosting (XGBoost) Algorithm and Mutual Information for Feature Selection by Regitha Zizilia, Yulison Herry Chrisnanto, Gunawan Abdillah

“…This study aims to evaluate the impact of feature selection using Mutual Information on the performance of lung cancer classification with the XGBoost algorithm. Mutual Information is employed to select relevant features, including those with linear and non-linear relationships with the target variable, while XGBoost is chosen for its ability to handle large datasets and reduce overfitting. …”
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A Lightweight Citrus Ripeness Detection Algorithm Based on Visual Saliency Priors and Improved RT-DETR by Yutong Huang, Xianyao Wang, Xinyao Liu, Liping Cai, Xuefei Feng, Xiaoyan Chen

“…Additionally, the Inner-SIoU loss function was employed for bounding box regression, while a weight initialization method based on visual saliency maps was proposed. …”
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Artificial Intelligence Algorithms in Asthma Management: A Review of Data Engineering, Predictive Models, and Future Implications by Shayma Alkobaisi, Muhammad Farhan Safdar, Piotr Pałka, Najah Abed Abu Ali

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Design Optimization of Secondary Element of Single-Sided Linear Induction Motors Using a Genetic Algorithm by V. A. Prakht, V. V. Goman, A. S. Paramonov

“…The article focuses on the use of genetic algorithms for the design of linear induction motors. …”
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Advances in Neuroimaging and Deep Learning for Emotion Detection: A Systematic Review of Cognitive Neuroscience and Algorithmic Innovations by Constantinos Halkiopoulos, Evgenia Gkintoni, Anthimos Aroutzidis, Hera Antonopoulou

“…It, therefore, aims to merge cognitive neuroscience insights with advanced algorithmic methods in pursuit of an enhanced understanding and applications of emotion recognition. …”
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GCS-YOLO: A Lightweight Detection Algorithm for Grape Leaf Diseases Based on Improved YOLOv8 by Qiang Hu, Yunhua Zhang

“…In view of the issues of high complexity, significant computational resource consumption, and slow inference speed in the detection algorithm for grape leaf diseases, this paper proposes GCS-YOLO, a lightweight detection algorithm based on an improved YOLOv8. …”
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A steady state micro genetic algorithm for hyper-heuristic generation in one-dimensional bin packing by Julio Juárez, Jesús Guillermo Falcón-Cardona, José Carlos Ortiz-Bayliss

“…Its primary objective is to allocate items into bins while minimizing the number of bins used. Due to the complexity of the problem, exact algorithms are often impractical for large instances, which has led to a reliance on tailored heuristics that may perform well on some instances but poorly on others. …”
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Performance Comparison of Vertex Block Descent and Position Based Dynamics Algorithms Using Cloth Simulation in Unity by Jun Ma, Nak-Jun Sung, Min-Hyung Choi, Min Hong

“…The results indicate that while the performance difference in frames per second (fps) between the two algorithms is negligible for simulations with a small number of nodes, the VBD algorithm consistently outperforms the PBD algorithm as the node count increases. …”
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