Multi-Task Water Quality Colorimetric Detection Method Based on Deep Learning by Shenlan Zhang, Shaojie Wu, Liqiang Chen, Pengxin Guo, Xincheng Jiang, Hongcheng Pan, Yuhong Li

“…Experimental results demonstrate that the optimized deep learning algorithm excels in precision (96.4%), recall (96.2%), and mAP50 (98.3), significantly outperforming other mainstream models. …”
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Numerical Investigation on Influential Factors for Quality of Smooth Blasting in Rock Tunnels by Baoping Zou, Zhipeng Xu, Jianxiu Wang, Zhanyou Luo, Lisheng Hu

“…As prerequisite for the evaluation of the blasting quality, effective identification of the influential factors affecting smooth blasting usually plays a significant role in the improvement of smooth blasting design. Compared to the expensive and time-consuming experiments including physical modelling and field tests, numerical modelling, as a cost-efficient approach, offers an attractive alternative to investigate the influential factors in terms of weight, which might be more applicable and reliable for the optimization of smooth blasting parameters. …”
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Enhancing high pressure pulsation test bench performance: a machine learning approach to failure condition tracking by Aslı Aksoy, Ömer Haki

“…Decision tree (DT), gradient boosting tree (GBT), Naïve Bayes (NB), and random forest (RF) algorithms are used to determine the best model. The comparative analysis of ML algorithms revealed that the GBT algorithm exhibits superior predictive capabilities regarding HPPT bench failure predictions. …”
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Electric Submersible Pump Fault Diagnosis Based on Laplacian Eigenmaps and Weighted Extreme Learning Machine by XU Zekun, FU Jun, GAO Xiaoyong, ZHANG Yu, LI Qiang, TAN Chaodong

“…In response to the serious imbalance in the data collected by ESP, firstly, a fault diagnosis model is established using a weighted extreme learning machine; Then, to solve the problems of insufficient algorithm learning, high computational costs caused by weighted strategies, and poor performance in applying to high-dimensional feature spaces, the Laplacian eigenmaps method is introduced to further optimize the model; finally, the effectiveness of the proposed method was validated on the TE chemical process dataset, and the practicality of the algorithm was experimentally validated on the real-time fault dataset of electric submersible pump. …”
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Tracking and Disturbance Suppression of the Radio Telescope Servo System Based on the Equivalent-Input-Disturbance Approach by Lei Yang, Na Wang, Zhiyong Liu, Ning Li

“…An EID estimator is developed using the difference between the estimated output of the state observer and the measurement output and then the estimate of the EID is fed forward into the control input to reject the disturbance. A cost function with clear physical meaning is selected and the weighting parameters are adjusted for the optimal controller to improve tracking performance. …”
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Intelligent Charging Navigation for Electric Vehicles Based on Real-time Electricity Price by Rui WU, Liangsong ZHOU, Zhandong YAO

“…The simulation results show that the method can reduce the travel cost of EV users and improve the node voltage quality of the power distribution system.…”
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Multi-Level Spectral Attention Network for Hyperspectral BRDF Reconstruction from Multi-Angle Multi-Spectral Images by Liyao Song, Haiwei Li

“…Then, the radiance consistency of BRDF multi-angle data is effectively optimized, the error caused by illumination variation in BRDF modeling is reduced, and the accuracy of BRDF modeling is improved. …”
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The analysis of fraud detection in financial market under machine learning by Jing Jin, Yongqing Zhang

“…Although the Stacking model has challenges in computing cost and delay, its advantages in fraud detection accuracy and robustness make it a powerful tool for financial institutions to improve their risk control ability. …”
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Sonar-Based Simultaneous Localization and Mapping Using the Semi-Direct Method by Xu Han, Jinghao Sun, Shu Zhang, Junyu Dong, Hui Yu

“…To obtain better feature extraction results in specific directions, we propose a method that accelerates the computation of the two-dimensional SO-CFAR algorithm, with the time cost being only a very slight increase compared to the one-dimensional SO-CFAR. …”
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Coal mining equipment lifecycle management system architecture and key technology by Yihui PANG, Jinglong BI, Pengzhe YUAN, Baofu ZHAO, Ziwei DING

“…Analyzed the current status and existing problems of coal mining equipment state perception technology, studied indirect perception methods based on non-contact sensing technology, and reduced installation and operation costs while improving solution accuracy. We studied the technical path of remote operation and maintenance of physical models based on digital twin technology, proposed a geometric-mechanism-data model fusion driven operation control and maintenance strategy, and looked forward to the development direction of intelligent comprehensive management technology and system platform for the entire life cycle of coal mining equipment.…”
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Intelligent deep learning-based dual-task approach for robust power quality event classification by Lipsa Ray, Pampa Sinha, Siddhanta Pani, Anshuman Nayak, Kaushik Paul, Chitralekha Jena, Md. Minarul Islam, Taha Selim Ustun

“…These findings underscore the model’s efficacy in real-time PQ monitoring, contributing to improved reliability and stability in evolving power systems.…”
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Lightweight YOLOv8s-Based Strawberry Plug Seedling Grading Detection and Localization via Channel Pruning by CHEN Junlin, ZHAO Peng, CAO Xianlin, NING Jifeng, YANG Shuqin

“…To improve the detection efficiency and reduce the model's computational cost, the layer-adaptive magnitude-based pruning(LAMP) score-based channel pruning algorithm was applied to compress the base YOLOv8s model. …”
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Enhancing the e-commerce shopping experience with IoT-enabled smart carts in smart stores by Jian Wang

“…The findings demonstrate that the proposed IoT-enabled model efficiently balances classification tasks, reduces congestion during algorithm execution, and minimizes energy waste. …”
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Spatiotemporal-Dependent Vehicle Routing Problem Considering Carbon Emissions by Ziqi Liu, Yeping Chen, Jian Li, Dongqing Zhang

“…Then, we establish a mixed-integer nonlinear programming model with minimum distribution costs including transportation costs, carbon emissions costs, and penalty costs on earliness and tardiness. …”
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Interactive Operation Strategy for Multi-scenario County-Level Multi-microgrid Based on ADMM by Chongbiao ZHANG, Chenwen QIAN, Hongyan YU, Yanling PENG, Jinwei CHEN

“…Firstly, a scheduling model for independent microgrid operation is established to realize the optimal scheduling strategy in the day-ahead pre-scheduling plan. …”
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Optimasi Algoritma Naive Bayes dengan Diskritisasi K-Means pada Diagnosis Penyakit Jantung by Nafa Fajriati, Budi Prasetiyo

“…Naïve Bayes is a classification algorithm that has a fairly good ability to build a classifier model. …”
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A Dynamic Adaptive Ensemble Learning Framework for Noninvasive Mild Cognitive Impairment Detection: Development and Validation Study by Aoyu Li, Jingwen Li, Yishan Hu, Yan Geng, Yan Qiang, Juanjuan Zhao

“…Finally, the accuracy and efficiency of the classification model were improved by optimizing the combination of base learners. …”
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Research on Near-Infrared Non-Invasive Blood Glucose Detection Technology by Wang Jinshuo

“…In response to the complex and easily interfered characteristics of near-infrared spectral signals, an innovative BP neural network algorithm is introduced to construct a prediction model. …”
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Revolutionizing Supply Chain Management With AI: A Path to Efficiency and Sustainability by Kassem Danach, Ali El Dirani, Hassan Rkein

“…Through an in-depth analysis of various AI techniques—such as machine learning, predictive analytics, and optimization algorithms—this study offers novel insights into their applicability in solving complex supply chain problems like demand forecasting, inventory management, and logistics optimization. …”
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Research on Self-Diagnosis and Self-Healing Technologies for Intelligent Fiber Optic Sensing Networks by Ruiqi Zhang, Liang Fan, Dongzhu Lu

“…Unlike traditional self-diagnosis techniques that rely on an optical time domain reflectometer, the proposed self-diagnosis algorithm utilizes data structure analysis, significantly reducing dependence on costly equipment and improving self-diagnosis efficiency. …”
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