Deep Reinforcement Learning Assisted UAV Path Planning Relying on Cumulative Reward Mode and Region Segmentation by Zhipeng Wang, Soon Xin Ng, Mohammed EI-Hajjar

“…The proposed region segmentation algorithm and cumulative reward model have been tested in different DRL techniques, where we show that the cumulative reward model can improve the training efficiency of deep neural networks by 30.8% and the region segmentation algorithm enables deep Q-network agent to avoid 99% of local optimal traps and assists deep deterministic policy gradient agent to avoid 92% of local optimal traps.…”
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Laser-induced Breakdown Spectroscopy Based on Pre-classification Strategy for Quantitative Analysis of Rock Samples by Weiheng KONG, Lingwei ZENG, Yu RAO, Sha CHEN, Xu WANG, Yanting YANG, Yixiang DUAN, Qingwen FAN

“…Different element quantitative models were constructed for each rock type. The kNN algorithm was selected using cross-validation to determine the optimal k value, and the key punishment parameter C and RBF width parameter γ of the SVM algorithm were determined using a grid search method. …”
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Mixed reality infrastructure based on deep learning medical image segmentation and 3D visualization for bone tumors using DCU-Net by Kun Wang, Yong Han, Yuguang Ye, Yusi Chen, Daxin Zhu, Yifeng Huang, Ying Huang, Yijie Chen, Jianshe Shi, Bijiao Ding, Jianlong Huang

“…Conclusion: The deep learning DCU-Net algorithm model can improve the performance of tumor CT image segmentation, and the reconstructed fine model can better reflect the actual situation of individual tumors; the MR system constructed based on this model enhances clinicians’ understanding of tumor morphology and spatial relationships. …”
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RFID-Based Real-Time Salt Concentration Monitoring with Adaptive EKF by Renhai Feng, Xinyi Lin

“…This paper presents a novel RFID wireless sensing system for noninvasive solution concentration monitoring, combining physical modeling with advanced estimation algorithms. By combining the Cole–Cole model and the slit cylindrical capacitor (SCC) model, the system establishes physics-based state-space models to characterize concentration-dependent RFID signal variations. …”
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Enhancing DeepLabv3+ Convolutional Neural Network Model for Precise Apple Orchard Identification Using GF-6 Remote Sensing Images and PIE-Engine Cloud Platform by Guining Gao, Zhihan Chen, Yicheng Wei, Xicun Zhu, Xinyang Yu

“…This study enhanced the DeepLabv3+ model to achieve superior performance in apple orchard identification by incorporating ResNet, optimizing the algorithm, and adjusting hyperparameter configuration using the PIE-Engine cloud platform. …”
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Long Short-Term Memory–Model Predictive Control Speed Prediction-Based Double Deep Q-Network Energy Management for Hybrid Electric Vehicle to Enhanced Fuel Economy by Haichao Liu, Hongliang Wang, Miao Yu, Yaolin Wang, Yang Luo

“…The initial learning rate and dropout probability of the LSTM speed prediction model are optimized using a Double Deep Q-Network (DDQN) algorithm. …”
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Risk prediction of hyperuricemia based on particle swarm fusion machine learning solely dependent on routine blood tests by Min Fang, Chengjie Pan, Xiaoyi Yu, Wenjuan Li, Ben Wang, Huajian Zhou, Zhenying Xu, Genyuan Yang

“…Subsequently, a risk prediction model is constructed based on the parameter optimization of five machine learning models using the PSO algorithm. …”
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Methods of Machine-Aided Training in Small Business: Content and Management by S. A. Tishchenko, M. A. Shakhmuradian

“…The authors conducted a formal and analytical review of potential means for small business optimization. They described types of algorithms and models of machine-aided training, such as multiple regressive model, logistic regression, etc., as well as instrumental problems of their use by enterprise analysts and developers. …”
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Spaceborne THz-ISAR Imaging of Space Target with Joint Motion Compensation Based on FrFT and GWO by Ao Zhou, Qi Yang, Zhian Yuan, Hongqiang Wang, Jun Yi, Shuangxun Li

“…Due to the high rendezvous speed and the short wavelength of THz radar, the traditional stop-and-go model, along with its supporting algorithms, is not applicable. …”
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Real-time temperature prediction of large-scale lithium battery module driven by data based on few measurement points by Jiajie HAN, Qingyang YUAN, Yu LI, Bo ZHANG, Ke XUE, Tian LAN

“…This slight error increase is attributed to the complex heat transfer dynamics near cooling interfaces, which pose challenges for most data-driven models. This study highlights the effectiveness of the Gappy POD algorithm in managing the thermal dynamics of large-scale energy storage systems in real time. …”
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CFD method for the effect of baffle locations and baffle lengths on the hydraulic characteristics of a horizontal sedimentation tank by T. Zhang, W. Wei, Y. Hong, J. Wang, J. Zhang, Y. Pei, Q. Li

“…The governing equations were discretized by using the finite volume method (FVM), the free water surface was tracked by the volume of fluid (VOF) method, and the coupling between velocity and pressure was solved by using the pressure implicit splitting-operator (PISO) algorithm. The results show that, in the design of baffle location and baffle length of a laboratory horizontal sedimentation tank, a baffle with a proper length and arranged at a certain proper distance horizontally away from the inlet of the tank will result in smallest circulation area in the flow field, and can effectively improve its operational efficiency; moreover, changing the length of the baffle cannot obviously reduce the circulation area, that is, the effect of baffle location is greater than that of baffle length on the hydraulic characteristics of a horizontal sedimentation. …”
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Application of machine learning for the analysis of peripheral blood biomarkers in oral mucosal diseases: a cross-sectional study by Huiyu Yao, Zixin Cao, Liangfu Huang, Haojie Pan, Xiaomin Xu, Fucai Sun, Xi Ding, Wan Wu

“…Future research should focus on validating these findings in larger cohorts and exploring alternative machine-learning algorithms to improve diagnostic accuracy further.…”
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Diagnosis of winter precipitation types using the spectral bin model (version 1DSBM-19M): comparison of five methods using ICE-POP 2018 field experiment data by W. Bang, J. T. Carlin, K. Kim, A. V. Ryzhkov, A. V. Ryzhkov, G. Liu, G. Lee

“…We thus explore the effects of the SBM's microphysics scheme on the extent of melting in cases of misdiagnosed RA. An optimized SBM that uses the climatological snow density–diameter relationship for the Pyeongchang region produces an increased amount of melting and achieves improved skill scores compared to the current SBM, which uses a snow density–diameter relationship for the Colorado region.…”
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Alpine Meadow Fractional Vegetation Cover Estimation Using UAV-Aided Sentinel-2 Imagery by Kai Du, Yi Shao, Naixin Yao, Hongyan Yu, Shaozhong Ma, Xufeng Mao, Litao Wang, Jianjun Wang

“…The results showed that: (1) Machine learning algorithms based on Sentinel-2 and UAV imagery effectively improved the accuracy of FVC estimation in alpine meadows. …”
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Research status of gearboxes for high-power nuclear power circulation pumps by WEI Fude, WANG Huanhuan, YANG Shuncheng

“…Many scholars are committed to in-depth research on high-power nuclear power circulating pump gearboxes from the perspectives of dynamics, mechanical design, big data, optimization algorithms, etc., in response to the above-mentioned issues. …”
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Machine learning as a tool for diagnostic and prognostic research in coronary artery disease by B. I. Geltser, M. M. Tsivanyuk, K. I. Shakhgeldyan, V. Yu. Rublev

“…It is assumed that the improvement of ML-based models and their introduction into clinical practice will help support medical decision-making, increase the effectiveness of treatment and optimize health care costs.…”
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Intelligent Scheduling of a Pulsating Assembly Flow Shop Considering a Multifunctional Automated Guided Vehicle by Hailong Song, Shengluo Yang, Shuoxin Yin, Junyi Wang, Zhigang Xu

“…Our experimental results demonstrate that the proposed strategies significantly improve the production efficiency of pulsating assembly workshops, reduce AGV scheduling costs, and optimize overall production workflows. …”
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A Matching Game for LLM Layer Deployment in Heterogeneous Edge Networks by Benedetta Picano, Dinh Thai Hoang, Diep N. Nguyen

“…Executing the inference of foundation models in a distributed manner presents significant challenges, particularly in optimizing both computing and communication resources. …”
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Adaptive method runtime safety assurance for autonomous driving in dynamic scenarios by XU Bingfeng, CHEN Jialing, YANG Shuailing, HE Gaofeng

“…In this model, a deep Q-network algorithm based on an adaptive dual-buffer prioritized experience replay mechanism was designed for the performance controller to enhance the adaptability of decision-making strategies in dynamic traffic environments and to optimize traffic efficiency. …”
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Deep neural network approach integrated with reinforcement learning for forecasting exchange rates using time series data and influential factors by T. Soni Madhulatha, Dr. Md. Atheeq Sultan Ghori

“…The algorithm leverages the strengths of both deep learning and reinforcement learning to achieve improved predictive accuracy and adaptability. …”
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