Improving Daily Precipitation Estimates by Merging Satellite and Reanalysis Data in Northeast China by Gaohong Yin, Yanling Zhang, Yuxi Cao, Jongmin Park

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OVERVIEW OF METHODS FOR IMPROVING THE VISUAL QUALITY OF IMAGES AND VIDEOS IN ADVERSE WEATHER CONDITIONS by P. A. Lyakhov, A. S. Ionisyan, V. V. Liutova, A. R. Orazaev

“…Conclusions are drawn about each of the types of algorithms.Conclusion The article explored various methods to improve the visual quality of images and videos in adverse weather conditions. …”
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Improved simulation of thunderstorm characteristics and polarimetric signatures with LIMA two-moment microphysics in AROME by C. David, C. Augros, B. Vié, F. Bouttier, T. Le Bastard

“…The microphysics scheme that represents clouds in the model partly contributes to the introduction of uncertainties in the simulations. …”
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A Crash Severity Prediction Method Based on Improved Neural Network and Factor Analysis by Chen Zhang, Jie He, Yinhai Wang, Xintong Yan, Changjian Zhang, Yikai Chen, Ziyang Liu, Bojian Zhou

“…Thus, to progress in this area, in this study, a thorough artificial neural network combined with an improved metaheuristic algorithm was developed and tested in terms of its structure, training function, factor analysis, and comparative results. …”
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Research on Mine-Personnel Helmet Detection Based on Multi-Strategy-Improved YOLOv11 by Lei Zhang, Zhipeng Sun, Hongjing Tao, Meng Wang, Weixun Yi

“…This article presents an enhanced algorithm based on YOLOv11n, referred to as GCB-YOLOv11. …”
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Research on soybean leaf disease recognition in natural environment based on improved Yolov8 by Chen Chen, Chen Chen, Xiaolei Lu, Lei He, Lei He, Ruoxue Xu, Ruoxue Xu, Yi Yang, Yi Yang, Jing Qiu, Jing Qiu

“…Experimental results demonstrate that YOLOv8-DML achieves a mAP50 of 96.9%, marking a 1.8% improvement over the original YOLOv8 algorithm, while also achieving an 18.6% reduction in parameters. …”
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Water Supply Scheduling for Cross-basin Reservoir Groups Based on Improved Scheduling Diagram by ZHAO Siqi, XU Wei, CHEN Si, WANG Sufan, YANG Yi

“…To exploit the scheduling potential of cross-basin reservoir groups by employing runoff information,this paper proposes an improved reservoir scheduling diagram to retain simplicity and intuitiveness.Taking the Xiajiankou,Fengyan,and Nanpeng reservoirs in Banan District of Chongqing as an example,it adopts the POA algorithm to build a joint scheduling model of water diversion and water supply for the cross-basin reservoir groups by a simulation-optimization approach.Meanwhile,three scenarios of the current situation scheduling,optimized scheduling with conventional scheduling diagrams,and optimized scheduling with improved scheduling diagrams are set up to evaluate the water diversion and supply performance of reservoirs and analyze the influence of uncertainty runoff information on the scheduling performance.The results are as follows:① The improved scheduling diagram performs best in the long series scheduling,and it can increase the annual average water supply of the reservoir group by 6.87% and reduce the abandoned water by 87.58% compared with the current situation scheduling;② In a dry year,the method can reduce 486.3×10⁴ m³ of water shortage and increase 477.6×10⁴ m³ of water for power generation based on the current situation scheduling;③ When considering the runoff information uncertainty,the water supply of the improved scheduling diagram is 3.37% lower than the ideal case but is still 5.96% more than the conventional optimization.The results are conducive to making scientific decisions and improving the water supply effect.…”
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Remaining Useful Life Prediction of Aero-Engine Based on Improved GWO and 1DCNN by Lihua Shen, Yucheng Wang, Baorui Du, Hailong Yang, He Fan

“…This study systematically addresses limitations in existing data-driven remaining useful life prediction methodologies through comprehensive optimizations spanning data preprocessing protocols and model architectural enhancements. To mitigate the local optimum entrapment inherent in deep learning hyperparameter optimization, an improved Gray Wolf Optimizer incorporating dynamic perturbation factors is proposed. …”
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An improved bistable stochastic resonance method and its application in early bearing fault diagnosis by Yonghui Zhao, Anqi Jiang, Wanlu Jiang, Enyu Tang, Xu Jiang, Xiaoyang Gu

“…To address these issues, this paper proposes an improved piecewise unsaturated bistable stochastic resonance (PUBSR) method, which employs an asymmetric potential function to effectively mitigate the output saturation problem of CBSR. …”
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Colony Binary Classification Based on Persistent Homology Feature Extraction and Improved EfficientNet by Zumin Wang, Ke Yang, Jie Tang, Jun Gao, Yuhao Zhang, Wei Xu, Chun-Ming Huang

“…The proposed approach achieves a high accuracy of 98.64%, a 10.29% improvement over the original classification model. …”
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Horizontal Control System for Maglev Ruler Based on Improved Active Disturbance Rejection Controller by Gengyun Tian, Chunlin Tian, Jiyuan Sun, Shusen Diao

“…Initially, a mathematical model is meticulously established based on the principles of magnetic circuits and dynamics. …”
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Surface Defect Detection for Small Samples of Particleboard Based on Improved Proximal Policy Optimization by Haifei Xia, Haiyan Zhou, Mingao Zhang, Qingyi Zhang, Chenlong Fan, Yutu Yang, Shuang Xi, Ying Liu

“…On the particleboard defect dataset with limited images, PPOBoardNet achieves a mean average precision (mAP) of 79.0%, representing a 5.3% performance improvement over the YOLO series of optimal detection models. …”
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Voice recognition enhancement by genetic algorithm by Mohamed Salah Salhi, Ali Hamdan Alenezi

“…The study proposes a hybrid model between SOM and GA to take advantage of each of their properties and improve recognition rates. …”
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Time Series Data Augmentation for Energy Consumption Data Based on Improved TimeGAN by Peihao Tang, Zhen Li, Xuanlin Wang, Xueping Liu, Peng Mou

“…Using deep learning algorithms to establish prediction models for sensor data is an effective approach; however, the performance of these models is significantly influenced by the quantity and quality of the training data. …”
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Improved YOLOv8s-based foreign object detection method for mine conveyor belts by LI Runze, GUO Xingge, YANG Fazhan, ZHAO Peipei, XIE Guolong

“…In low-illumination mine environments, conveyor belt foreign object detection algorithms suffer from insufficient extraction of global image features and an excessive number of model parameters. …”
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A Method for Recognizing Dead Sea Bass Based on Improved YOLOv8n by Lizhen Zhang, Chong Xu, Sai Jiang, Mengxiang Zhu, Di Wu

“…The number of model parameters and GFLOPs were reduced by 23.3% and 18.5%, respectively, and the detection speed was improved from the original 304.5 FPS to 424.6 FPS. …”
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Truck Lifting Accident Detection Method Based on Improved PointNet++ for Container Terminals by Yang Shen, Xintai Man, Jiaqi Wang, Yujie Zhang, Chao Mi

“…To tackle these challenges, this paper proposes an accident detection method based on multi-line LiDAR and an improved PointNet++ model. This method uses multi-line LiDAR to collect point cloud data from operational lanes in real time and enhances the PointNet++ model by integrating a multi-layer perceptron (MLP) and a mixed attention mechanism (MAM), optimizing the model’s ability to extract local and global features. …”
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Fruit fast tracking and recognition of apple picking robot based on improved YOLOv5 by Yao Xu, Liu Zuodong

“…Compared with other models tested on six types of apple picking methods, including the original YOLOv5 model as well as YOLOv3 and EfficientDet‐D0 algorithms, our improved model shows significant improvements in mAP by 1.95%, 17.6%, and 12.7% respectively. …”
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STBNA-YOLOv5: An Improved YOLOv5 Network for Weed Detection in Rapeseed Field by Tao Tao, Xinhua Wei

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Leveraging AHP and transfer learning in machine learning for improved prediction of infectious disease outbreaks by Reham Abdallah, Sayed Abdelgaber, Hanan Ali Sayed

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