Quantitative evaluation and obstacle factor diagnosis of drug regulatory capacity in China. by Mingming Zhai, Liwen Huang, Shijie Sun, Liying Cao, Xueqiong Yue, Yuanxia Hu

“…<h4>Methods</h4>Using the methods of literature research, expert interviews, investigation and analysis, the quantitative evaluation indicator system of supervision ability was established in all directions; the indicator data were collected and quantified; the indicator weight setting algorithm of the evaluation system was improved and the indicator weight was set by combining AHP and entropy method; the differences among eastern, central, and western provincial-level regions were analyzed by variance analysis; panel data were constructed for spatio-temporal evolution analysis; obstacle factor diagnosis model was used to analyze the obstacle factors.…”
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Outdoor location scheme with fingerprinting based on machine learning of mobile cellular network by Zhichao ZHOU, Yi FENG, Xiaohan XIA, Yuyao FENG, Chao CAI, Jiahui QIU, Lihui YANG, Yunxiao WU

“…The positioning scheme based on mobile cellular network technology is one of the important technical approaches to provide network optimization, emergency rescue, police patrol and location services.The traditional positioning scheme based on cell base station location information has low positioning accuracy and large positioning error, so it cannot meet the requirements of some positioning applications.The scheme based on fingerprint location can greatly improve the location accuracy, save computational cost and enhance the usability based on the coarse location scheme of the cell and become the hotspot of the research.Rasterization and non-rasterization of outdoor fingerprint location scheme based on machine learning were studied and analyzed to meet the business requirements of outdoor fingerprint location.By means of parameter weighting, data fitting and other methods, large-scale fingerprint data were cleaned to improve the effectiveness of data sources.Through the realization of sub-modules such as demarcating research area, rasterizing, constructing fingerprint database, training model, correcting model, non-rasterizing, rough positioning coupling, matching parameter and training parameter, the operation efficiency and positioning accuracy of the algorithm were analyzed and optimized, and the key indexes affecting the algorithm performance were determined.Then, the performance of two fingerprint-based localization schemewas analyzed based on the simulation results.Finally, the typical scenarios of the fingerprint location scheme based on machine learning in practical application were presented.…”
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Calculation Methods for the Permeability Coefficient of Concrete Face Rockfill Dam with Cracks by Zhongwen Shi, Zhongru Wu, Chongshi Gu, Bo Chen, Hailong Zhang, Wenzhong Yin, Bangbin Wu

“…This calculation helped simplify the establishment of a finite element model and improve the efficiency of calculating the seepage of dams. …”
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Torsional Stiffness Correction of the Split-Type Triple-Box Steel Box Girder Based on Refined Simulation by Yu Tang, Min Xu, Jie Yue, Shixiong Zheng

“…Then, the beam element is used for conventional modelling of the bridge, and artificial bee colony (ABC) algorithm is adopted for the optimization and correction of structure parameters of the BEM of the girder. …”
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Local pattern aware 3D video swin transformer with masked autoencoding for realtime augmented reality gesture interaction by Suli Wang

“…During data preprocessing, the study uses a synthetic data annotation method to automatically generate 3D gesture images and annotate joint information, significantly improving data annotation efficiency. Using weighted Euclidean distance and structural similarity optimization, the paper proposes an image denoising model based on maximum a posteriori probability that effectively reduces noise interference in gesture image analysis. …”
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Perception Error-resistant Air Combat Maneuvering Decisions Based on Deep Reinforcement Learning by Chengbin TIAN, Hui LI, Xiliang CHEN, Fengguo WU

“…In response to this issue, an algorithm based on Proximal Policy Optimization (PPO) is proposed using features extracted by a Gated Recurrent Unit (GRU). …”
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Few-Shot Intelligent Anti-Jamming Access with Fast Convergence: A GAN-Enhanced Deep Reinforcement Learning Approach by Tianxiao Wang, Yingtao Niu, Zhanyang Zhou

“…Under dynamic jamming and intelligent jamming, the algorithm significantly outperforms the DQN, Proximal Policy Optimization (PPO), and Q-learning (QL) algorithms.…”
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Stroke Risk Classification Using the Ensemble Learning Method of XGBoost and Random Forest by Gullam Almuzadid, Egia Rosi Subhiyakto

“…This study proposes a stroke risk classification model using ensemble learning that combines Random Forest and XGBoost algorithms. …”
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Multi-Source, Fault-Tolerant, and Robust Navigation Method for Tightly Coupled GNSS/5G/IMU System by Zhongliang Deng, Zhichao Zhang, Zhenke Ding, Bingxun Liu

“…Compared with standard Kalman filtering (EKF) and advanced multi-rate Kalman filtering (MRAKF), the proposed algorithm achieved 28.3% and 53.1% improvements in its <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>1</mn><mi>σ</mi></mrow></semantics></math></inline-formula> error, respectively, significantly enhancing the accuracy and reliability of the multi-source fusion navigation system.…”
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A Two-Stage Site Selection and Capacity Determination Method for Energy Storage Power Stations Based on HC-MOPSO by Wangwang BAI, Dezhou YANG, Wanwei LI, Tao WANG, Yaozhong ZHANG

“…The MOPSO algorithm embedded in power flow calculation is designed to solve the model. …”
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Multivariate Load Forecasting of Integrated Energy System Based on CEEMDAN-CSO-LSTM-MTL by WANG Yongli, LIU Zeqiang, DONG Huanran, LI Dexin, CHEN Xin, GUO Lu, WANG Jiarui

“…Based on this，a comprehensive energy system short-term load forecasting model is proposed，which combines complete ensemble empirical mode decomposition with adaptive noise （CEEMDAN），cross optimization algorithm （CSO），long short term memory （LSTM） network，and multi task learning （MTL）. …”
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Design and Implementation of Local Threshold Segmentation Based on FPGA by Shangshang Gao, Yuanyuan Wang, Zhaofeng Chen, Feng Zhou, Rugang Wang, Naihong Guo

“…Finally, the design algorithm is verified by ModelSim simulation software and QT5 software. …”
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Enhancing Consumer Decision-Making in Skincare: Implementation of the VIKOR Method for Product Recommendation Systems by Diah Arifah Prastiningtyas, Greta Septy Purwiantono, Febry Eka Purwiantono, Addin Aditya

“…By demonstrating the efficacy of the VIKOR method, this research paves the way for its future application in various industries, offering a replicable and adaptable model for improving decision processes in consumer goods selection across diverse markets. …”
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A Fault Detection Framework for Rotating Machinery with a Spectrogram and Convolutional Autoencoder by Hoyeon Lee, Jaehong Yu

“…In modern industrial systems, establishing the optimal maintenance policy for rotating machinery is essential to improve productivity and prevent catastrophic accidents. …”
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Intelligent Trust Evaluation Method for Underwater Sensor Networks Based on Fuzzy Clustering and Dynamic Weight Allocation by Zhaohui WANG, Guangjie HAN, Jiaxin DU, Chuan LIN, Lei WANG

“…Then, the unsupervised machine learning algorithm, namely fuzzy C-means clustering, was employed to enable adaptive node trust decision-making. …”
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Implications of machine learning techniques for prediction of motor health disorders in Saudi Arabia by Ehab M. Almetwally, I. Elbatal, Mohammed Elgarhy, Amr R. Kamel

“…Decisions are made easier and social health care is improved with the help of this system because timely interventions are implemented, patient outcomes are improved, and resource allocation is optimized.…”
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Intra-day dispatch method via deep reinforcement learning based on pre-training and expert knowledge by Yanbo Chen, Qintao Du, Huayu Dong, Tao Huang, Jiahao Ma, Zitao Xu, Zhihao Wang

“…In recent years, due to high self-learning and self-optimization ability, reinforcement learning has emerged in the field of economic dispatch, which can solve model-free dynamic programming problems that cannot be effectively solved by traditional optimization methods. …”
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Short-Term Traffic Flow Prediction: A Method of Combined Deep Learnings by Chuanxiang Ren, Chunxu Chai, Changchang Yin, Haowei Ji, Xuezhen Cheng, Ge Gao, Heng Zhang

“…Then, the neuron number, loss function, optimization algorithm, and other parameters of the CDLP model are discussed and set through experiments. …”
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ADAM-DETR: an intelligent rice disease detection method based on adaptive multi-scale feature fusion by Hanyu Song, Xinyue Huang, Ziqiang Wang, Jianwei Hu, Huasheng Zhang, Hui Yang

“…The algorithm innovatively designs three core modules: the AdaptiveVision Network (AVN) backbone for enhanced feature extraction, the Dual-Domain Enhanced Transformer (DDET) module for spatiotemporal-frequency domain collaboration, and the Adaptive Multi-scale Feature Model (AMFM) for improved feature fusion. …”
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Rolling Bearing Fault Diagnosis Method Based on Fusion of CNN and CSSVM by LI Yunfeng, LAN Xiaosheng, SHEN Hongchang, XU Tongle

“…The results show that the combination of convolutional neural network to extract fault features and parameters to optimize the classification model structure of support vector machine can not only improve the diagnostic accuracy, but also have strong generalization performance.…”
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