Review: the application of deep reinforcement learning to quantitative trading in financial market by XU Bo, HE Yijun, WEN Jiancheng, LI Xiangxia

“…It is believed that with the continuous optimization of algorithms and the improvement of computing power, DRL will play a more important role in the field of quantitative trading in financial market, providing more accurate and reliable support for investment decisions.…”
Get full text

Federated deep reinforcement learning-based edge collaborative caching strategy in space-air-ground integrated network by LIU Liang, JING Tengxiang, DUAN Jie, MAO Wuping, YAN Hongcheng, MA Wenjie

“…Simulation results show that compared with other algorithm, the proposed algorithm can improve the cache hit rate of user requests by 18% and reduce the access latency of content by 25% while protecting user privacy.…”
Get full text

Design of 3D Environment Combining Digital Image Processing Technology and Convolutional Neural Network by Xiaofei Lu, Shouwang Li

“…To enhance 3D reconstruction accuracy, this study proposes a digital image processing technology that combines binocular camera calibration, stereo correction, and a convolutional neural network (CNN) algorithm for optimization and improvement. By employing the refined stereo-matching algorithm, a 3D reconstruction model was developed to augment 3D environment design and reconstruction accuracy while optimizing the 3D reconstruction effect. …”
Get full text

Transient stability assessment of wind turbine grid-connected systems using ISSA-MSVR by FAN Hong, XU Yongjie, XU Tao

“…To address the issue of inaccurate transient stability analysis in power systems after wind farm integration， this paper proposes a method combining improved sparrow search algorithm （ISSA）-optimized multi-output support vector regression （MSVR）. …”
Get full text

A hybrid approach to predicting and classifying dental impaction: integrating regularized regression and XG boost methods by Asok Mathew, Pradeep K. Yadalam, Ahmed Radeideh, Shrouk Hady, Rona Swed, Reyyan Cheema, Majd Mousa AL-Mohammad, Mohammed Alsaegh, SR Shetty

“…Enhancing data quality, refining feature selection, and using advanced modeling techniques are crucial for improving predictive capabilities. …”
Get full text

Machine learning and transfer learning techniques for accurate brain tumor classification by Seyed Matin Malakouti, Mohammad Bagher Menhaj, Amir Abolfazl Suratgar

Get full text

The Bridge between Screening and Assessment: Establishment and Application of Online Screening Platform for Food Risk Substances by Kang Hu, Shaoming Jin, Hong Ding, Jin Cao

“…The screening comparison algorithm, the core of the screening model, is obtained through the improvement of the existing spectral library search algorithm. …”
Get full text

Fault diagnosis method of timing signal based on Nadam-TimeGAN and XGBoost by HEI Xinhong, GAO Miao, ZHANG Kuan, FEI Rong, QIU Yuan, JI Wenjiang

“…The Nadam optimization algorithm was used to optimize the components of the TimeGAN model, that was, the Nadam-TimeGAN model was constructed for data expansion. …”
Get full text

A Time-Dependent Fuzzy Programming Approach for the Green Multimodal Routing Problem with Rail Service Capacity Uncertainty and Road Traffic Congestion by Yan Sun, Martin Hrušovský, Chen Zhang, Maoxiang Lang

“…Two uncertain factors, including capacity uncertainty of rail services and travel time uncertainty of road services, are formulated in order to improve the reliability of the routes. By using the triangular fuzzy numbers and time-dependent travel time to separately model the capacity uncertainty and travel time uncertainty, we establish a fuzzy chance-constrained mixed integer nonlinear programming model. …”
Get full text

Computational design exploration of rocket nozzle using deep reinforcement learning by Aagashram Neelakandan, Arockia Selvakumar Arockia Doss, Natrayan Lakshmaiya

“…Additionally, the use of the Single-Step Proximal Policy Optimization (SSPPO) algorithm enhances the exploration of nozzle geometries by maximizing aerodynamic performance while balancing computational efficiency. …”
Get full text

Methods to Quantitatively Evaluate the Effect of Shale Gas Fracturing Stimulation Based on Least Squares by DENG Cai, SUN Kexin, WEN Huan, HU Chaolang

“…This study develops a comprehensive, physics-based quantitative model to accurately evaluate the effectiveness of fracturing stimulation, enabling data-driven optimization of shale gas extraction processes.MethodsThis study established a novel quantitative evaluation model based on principles of fluid mechanics and mathematical optimization theory. …”
Get full text

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.…”
Get full text

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.…”
Get full text

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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

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). …”
Get full text

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.…”
Get full text

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. …”
Get full text

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. …”
Get full text