Reinforcement Learning for Computational Guidance of Launch Vehicle Upper Stage by Shiyao Li, Yushen Yan, Hao Qiao, Xin Guan, Xinguo Li

“…This manuscript investigates the use of a reinforcement learning method for the guidance of launch vehicles and a computational guidance algorithm based on a deep neural network (DNN). Computational guidance algorithms can deal with emergencies during flight and improve the success rate of missions, and most of the current computational guidance algorithms are based on optimal control, whose calculation efficiency cannot be guaranteed. …”
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Enhancing the Green Construction Performance Resilience in Infrastructure Projects: A Complexity Perspective by Yikun Su, Junhao Liu, Zhizhe Zheng

“…The optimization algorithm has been validated and shown to improve the GCPR level of the project. …”
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Cluster channel equalization using adaptive sensing and reinforcement learning for UAV communication by Xin Liu, Shanghong Zhao, Yanxia Liang, Shahid Karim

“…Finally, we construct the U-FRQL-EA equalization algorithm by combining the improved U-Net model with fuzzy reinforcement Q-learning. …”
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Real-time Detection of Imperfect Wheat Grains on Wheat Pile Surface Based on IDS-YOLO by FAN Jiawei, WU Lan, YAN Jingjing

“…To address the high missed detection rate of imperfect grains in target detection algorithms and to enhance the model detection speed, this study optimized the lightweight network model YOLOV4-Tiny. …”
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Microservice selection approach for mobile users in edge computing environment by ZHAO Shuxu, JIANG Kaijun, WANG Xiaolong

“…Furthermore, a microservice selection algorithm was proposed based on the cloud-edge speedup model and a dynamic cloud-edge migration strategy to handle cross-domain migration under user mobility. …”
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2HR-Net VSLAM: Robust visual SLAM based on dual high-reliability feature matching in dynamic environments. by Wang Yang, Huang Chao, Zhang Yi, Tan Shuyi

“…Finally, the shared matching Siamese network with a unique dual-branch feature fusion strategy and similarity optimization algorithm is proposed to enhance the accuracy of feature matching. …”
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Technology for risk assessment at product lifecycle stages using fuzzy logic by A. N. Chesalin, S. Ya. Grodzenskiy, Pham Van Tu, M. Yu. Nilov, A. N. Agafonov

“…The problem of risk assessment at the stages of the product life cycle using both qualitative and quantitative approaches is investigated, and a generalized algorithm for selecting a fuzzy risk assessment model with different input data and system requirements is proposed for the effective use of statistical information and expert assessments. …”
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Deformation Characteristic Analysis and Engineering Application of a Variable Cross-sectional Flexible Pin by Chen Hengjian, Xiao Shuhong

“…The effectiveness of this method is verified by comparing with the calculation results of the engineering algorithm and the finite element method. The simulation model of the wind power gearbox is established using Romax software, and it is verified that the deformation characteristics of the variable cross-sectional flexible pin can improve the load distribution and load sharing coefficient. …”
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Prediction of Bus Arrival Time Based on Gated Recurrent Unit Neural Networks by LU Juntian;SUN Ling;SHI Quan

“…Furthermore, combining more than 50 million pieces of raw data, the model uses Spark elastic distributed data set in distributed Hadoop cluster to clean data and site matching algorithm to match source data, Lasso algorithm to optimize feature options and remove interference. …”
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Forecast of Photovoltaic Power Based on IWPA-LSSVM Considering Weather Types and Similar Days by Yilun XU, Binqiao ZHANG, Jing HUANG, Xiao XIE, Ruoxin WANG, Danqing SHEN, Lina HE, Kaifan YANG

“…In order to improve the prediction accuracy of photovoltaic power, the input of the photovoltaic power prediction model is determined according to the characteristics of photovoltaic output power under different weather types. …”
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A Semi-Supervised Abbreviation Disambiguation Method Based on ACNN and Bi-LSTM by ZHANG Chun-xiang, PANG Shu-yang, GAO Xue-yao

“…Training corpus is extended by using Xgboost algorithm and LightGBM algorithm， and then expanded training corpus is input into this model. …”
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功率二分支齿轮传动系统两相遗传算法优化设计研究 by 贾驰, 王三民, 袁茹

“…Split-torque gear transmission is widely used in power transmission of shipbuilding and aviation.Studying on its optimal design has a huge significance on further reducing weight and improving load capacity.With considering dual-path split-torque gear transmission as the study object,choosing two-phase genetic algorithm which is based on the theory of punctuated equilibrium as optimization method,and taking minimum volume of gear transmission system as target function,in the premise of ensuring gear non-interference,teeth fitting,strength requirement conditions and so on,a dual-path split-torque gear transmission optimization model is established,and a optimal result is obtained.The result shows that two-phase genetic algorithm has a better optimal capacity,and the gear volume using this message has a 20% drop-off compared with conventional design.…”
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Adaptive robust self‐scheduling for a wind‐based GenCo equipped with power‐to‐gas system and gas turbine to participate in electricity and natural gas markets by Mojtaba Fereydani, Mohammad Amin Latify

“…A column & constraint generation (C&CG) algorithm is used to solve the model. Numerical results demonstrate the model’s effectiveness in various case studies, showing that the GenCo can manage wind uncertainties, benefit from arbitrage opportunities in electricity and gas markets, and improve economic outcomes. …”
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High-throughput end-to-end aphid honeydew excretion behavior recognition method based on rapid adaptive motion-feature fusion by Zhongqiang Song, Jiahao Shen, Qiaoyi Liu, Wanyue Zhang, Ziqian Ren, Kaiwen Yang, Xinle Li, Jialei Liu, Fengming Yan, Wenqiang Li, Yuqing Xing, Lili Wu

“…Compared with the model excluding the RK50 module, the mAP50 improved by 2.9%, and its performance in detecting small-target honeydew significantly surpassed mainstream algorithms. …”
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AI-Assisted Pump Operation for Energy-Efficient Water Distribution Systems by Niuosha Hedaiaty Marzouny, Rebecca Dziedzic

“…The LLM-assisted framework was compared with a genetic algorithm optimization. The results demonstrated that the proposed method outperformed the GA, achieving an energy reduction of 66.98%.…”
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Broiler Behavior Detection and Tracking Method Based on Lightweight Transformer by Haixia Qi, Zihong Chen, Guangsheng Liang, Riyao Chen, Jinzhuo Jiang, Xiwen Luo

“…In addition, we propose a new cross-scale feature fusion network to optimize the neck network of the original model. These improvements led to a 78% decrease in the number of parameters and a 68% decrease in GFLOPs. …”
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Research on Designing an Industrial Product-Service System with Uncertain Customer Demands by Fei Zhang, Liecheng Jia, Weizhen Han

“…This paper presents a design model that integrates an improved affinity propagation (AP) clustering algorithm, quality function development (QFD), and axiomatic design (AD). …”
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Communication resource allocation method in vehicular networks based on federated multi-agent deep reinforcement learning by Qingli Liu, Yongjie Ma

“…Finally, the global model parameters are fed back to the vehicles to further optimize the local resource allocation strategy, thus improving the system spectrum efficiency. …”
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High precision water quality retrieval in Dianchi Lake using Gaofen 5 data and machine learning methods by Yuewen Feng, Jun Zhang, Sanjie Guo, Yunbai Zhang, Zhongwei Zhang

“…The Back Propagation Nondominated Sorting Genetic Algorithm-II (BP-NGA) model consistently yielded positive results for most WQI. (2) Water quality in Dianchi varied significantly by region and season. (3) It was recommended to build wetlands and ecological parks on the southwest side of Dianchi and improve sewage interception pipelines on the northeast side to lessen the risk of eutrophication by reducing the inflow of nitrogen and phosphorus.…”
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Research on data completion and generation of downhole drilling tool attitude based on Long Short-Term Memory neural networks by Qiwei Liu, Fanmin Kong, Xiaolong Chen, Kang Li

“…To overcome these limitations, a Long Short-Term Memory (LSTM) model, a type of deep learning algorithm known for capturing complex time-series dependencies, is proposed for data completion. …”
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