Early Detection of Surface Mildew in Maize Kernels Using Machine Vision Coupled with Improved YOLOv5 Deep Learning Model by Yu Xia, Ao Shen, Tianci Che, Wenbo Liu, Jie Kang, Wei Tang

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An improved extreme learning machine algorithm for prospectivity mapping of copper deposits using multi-source remote sensing data: a case study in the North Altyn Tagh, Xinjiang,... by Boqi Yuan, Qinjun Wang, Wentao Xu, Chaokang He, Wenyue Xie

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SMEA-YOLOv8n: A Sheep Facial Expression Recognition Method Based on an Improved YOLOv8n Model by Wenbo Yu, Xiang Yang, Yongqi Liu, Chuanzhong Xuan, Ruoya Xie, Chuanjiu Wang

“…Additionally, the EfficiCIoU loss function replaces the original Complete IoU(CIoU) loss function, thereby improving bounding box localization accuracy and accelerating model convergence. …”
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Enhanced anomaly network intrusion detection using an improved snow ablation optimizer with dimensionality reduction and hybrid deep learning model by Fatimah Alhayan, Asma Alshuhail, Ahmed Omer Ahmed Ismail, Othman Alrusaini, Sultan Alahmari, Abdulsamad Ebrahim Yahya, Sami Saad Albouq, Mutasim Al Sadig

“…Finally, the improved Snow Ablation Optimizer (ISAO) model optimally tunes the hyperparameters of the LSTM–AE model, leading to enhanced classification performance. …”
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Integration of multi-temporal SAR data and robust machine learning models for improvement of flood susceptibility assessment in the southwest coast of India by Pankaj Prasad, Sourav Mandal, Sahil Sandeep Naik, Victor Joseph Loveson, Simanku Borah, Priyankar Chandra, Karthik Sudheer

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Time Series Prediction Method of Clean Coal Ash Content in Dense Medium Separation Based on the Improved EMD-LSTM Model by Kai Cheng, Xiaokang Zhang, Keping Zhou, Chenao Zhou, Jielin Li, Chun Yang, Yurong Guo, Ranfeng Wang

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Quaternion generative adversarial -driven Soc estimation using Tyrannosaurus optimizer for improving hybrid electric vehicles renewably powered energy management by M. Sivaramkrishnan, Jaganathan Subramani, Mohammad Mukhtar Alam, Liew Tze Hui

“…For more accurate SOC estimate, the proposed approach employs a Quaternion Generative Adversarial Network (QGAN) model. When hyper parameter tuning, the prototype is invigorated employing the Tyrannosaurus optimization algorithm (TOA) to fine-tune SOC estimate outcomes of the QGAN model. …”
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Hidden-layer configurations in reinforcement learning models for stock portfolio optimization by Patrick Kevin Aritonang, Sudarso Kaderi Wiryono, Taufik Faturohman

“…DDPG exhibited consistently strong performance, with its zero hidden-layer model showing the highest ASR. Conversely, PPO underperformed across all configurations, with negative returns in the zero-layer setup and marginal improvements with added complexity. …”
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A Method for Quantifying Mung Bean Field Planting Layouts Using UAV Images and an Improved YOLOv8-obb Model by Kun Yang, Xiaohua Sun, Ruofan Li, Zhenxue He, Xinxin Wang, Chao Wang, Bin Wang, Fushun Wang, Hongquan Liu

“…Compared with YOLOv8, YOLOv8-obb, YOLOv9, and YOLOv10, the YOLOv8-obb-p2 model improved precision by 1.6%, 0.1%, 0.3%, and 2%, respectively, and F1 scores improved by 2.8%, 0.5%, 0.5%, and 3%, respectively. …”
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Tramp Ship Routing and Scheduling with Integrated Carbon Intensity Indicator (CII) Optimization by Haiying Yang, Feiyang Ren, Jingbo Yin, Siqi Wang, Rafi Ullah Khan

“…This computational study, based on real historical data, verifies the effectiveness of the proposed model and algorithm. The results demonstrate notable improvements in fleet efficiency and environmental performance, increasing profitability by 4.38% while maintaining favorable CII ratings. …”
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Wind–Photovoltaic–Hydropower Joint Output Model Study Based on Probability Distribution and Correlation Analysis by Ligui Wu, Benhong Wang, Peng Zhang, Yiming Ke, Fangqing Zhang, Jiang Guo

“…Furthermore, the probability distribution of wind and photovoltaic output is calculated with the maximum likelihood method, and a correlation analysis between wind and photovoltaic output is conducted, where a wind–photovoltaic joint output model is established. Lastly, the k-means clustering algorithm is adopted to process typical scenarios of wind–photovoltaic joint output, and a case study is conducted to validate the wind–photovoltaic–hydropower joint output model. …”
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An Actor–Critic-Based Hyper-Heuristic Autonomous Task Planning Algorithm for Supporting Spacecraft Adaptive Space Scientific Exploration by Junwei Zhang, Liangqing Lyu

“…At the high level, a reinforcement learning strategy based on the actor–critic model is used, combined with the network architecture, to construct a framework for the selection of advanced heuristic algorithms. …”
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INFORMATION-ANALYTICAL MODEL FOR A FUZZY PROPORTIONALINTEGRAL-DERIVATIVE CONTROLLER by Timur T. Abduragimov, Vladimir B. Melekhin, Vyacheslav M. Hachumov

“…Objectives The aim of the study is to create a model allowing us to improve the accuracy of fuzzy control algorithms for complex objects in conditions of uncertainty. …”
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Research on Gating Fusion Algorithm for Power Grid Survey Data Based on Enhanced Mamba Spatial Neighborhood Relationship by Aiyuan Zhang, Jinguo Lv, Yu Geng, Xiaolei Wang, Xianhu Li

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Optimization of fuzzy bottleneck cost transportation models in the decision framework of congruence modulo technique by Kapil Kumar, Nandini, Tarun Kumar, Kailash Dhanuk, Anirudh Kumar Bhargava, M.K. Sharma

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Predictive analytics of complex healthcare systems using deep learning based disease diagnosis model by Muhammad Kashif Saeed, Alanoud Al Mazroa, Bandar M. Alghamdi, Fouad Shoie Alallah, Abdulrhman Alshareef, Ahmed Mahmud

“…To optimize the hyperparameter values of the CNN-LSTM approach, the Chaotic Tunicate Swarm Algorithm (CTSA) approach was implemented to improve the accuracy of classifier results. …”
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SSM-Net: Enhancing Compressed Sensing Image Reconstruction with Mamba Architecture and Fast Iterative Shrinking Threshold Algorithm Optimization by Xianwei Gao, Bi Chen, Xiang Yao, Ye Yuan

“…To address these challenges, this paper proposes SSM-Net, a novel framework that combines the state-space modeling (SSM) of the Mamba architecture with the fast iterative shrinking threshold algorithm (FISTA). …”
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Advancing Knowledge on Machine Learning Algorithms for Predicting Childhood Vaccination Defaulters in Ghana: A Comparative Performance Analysis by Eliezer Ofori Odei-Lartey, Stephaney Gyaase, Dominic Asamoah, Thomas Gyan, Kwaku Poku Asante, Michael Asante

“…The findings demonstrate that robust machine learning frameworks, combined with temporal and contextual feature engineering, can improve defaulter risk prediction accuracy. Integrating such models into routine immunization programs could enable data-driven targeting of high-risk groups, supporting policymakers in strategies to close vaccination coverage gaps.…”
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Analysis of the capabilities of an information system for improving sleep quality based on biometric data analysis by M.S. Graf, A.V. Yakoniuk, D.V. Krant, I.I. Golovach

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DMRG study of the theta-dependent mass spectrum in the 2-flavor Schwinger model by Etsuko Itou, Akira Matsumoto, Yuya Tanizaki

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