Prediction of Chemical Gas Emissions Based on Ecological Environment by Guobin Chen, Shijin Li

“…The prediction model, by using the relevant data collected by DCS as training samples and test samples, trains and tests the model. …”
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Form Grinding Simulation and Allowance Distribution Technique of Large Gear Ring by Luo Yong, Chen Weifang, Chen Qiwei, Su Chuan

“…Based on the grinding contact zone model,the grinding force model and the grinding and moving heat source theory,the simulation process of the deformation prediction of the ring gear grinding under the thermo-mechanical coupling is analyzed,and the optimization model of the gear grinding balance distribution is established. …”
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Prediction of hydrogen production in proton exchange membrane water electrolysis via neural networks by Muhammad Tawalbeh, Ibrahim Shomope, Amani Al-Othman, Hussam Alshraideh

“…The integration of artificial intelligence (AI) and machine learning (ML) appears to be effective in optimization within the energy sector. Hence, this work employs the artificial neural network (ANN) to develop a model that accurately predicts HPR in PEMWE setups. …”
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Deep Learning-Based Atmospheric Visibility Detection by Yawei Qu, Yuxin Fang, Shengxuan Ji, Cheng Yuan, Hao Wu, Shengbo Zhu, Haoran Qin, Fan Que

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Vibration Response of Small-caliber Vehicular Gun Tube with Gear Backlash by Fan Chunlin, Qiu Xiaobo, Shan Dongsheng, Wang Yang

“…Aiming at the study the vibration response frequency and its displacement of small-caliber vehicular gun tube,the simplified model of elevating mechanism including gear backlash is established and the method of parameter identification of contact-impact mechanical model is given.Through the dynamics simulation by applying sinusoidal signal in ADAMS,the vibration response frequency of tube with backlash are compared with no backlash,and its displacement and velocity are obtained.The results show that the continuous multi-frequency phenomenon occurred with large range,which has a bad effect on projectile initial conditions and reduces firing accuracy.Based on this,the theoretical guidance in structure optimization of gun control and firing accuracy improvement is provided.…”
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Dynamics Characteristic Analysis of Ball Screw Under High Load by Yang Wuxu, Fan Yuanxun, Liu Minghui, Dong Huili

“…To research the dynamics characteristic of high load ball screw under angular vibration driving velocity，a flexible body dynamic model and a control model considering the process of ball entering and leaving the re-circulating mechanism are built based on explicit time integration. …”
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Mapping Landslide Sensitivity Based on Machine Learning: A Case Study in Ankang City, Shaanxi Province, China by Baoxin Zhao, Jingzhong Zhu, Youbiao Hu, Qimeng Liu, Yu Liu

“…The main purpose of this research is to apply the logistic regression (LR) model, the support vector machine (SVM) model based on radial basis function, the random forest (RF) model, and the coupled model of the whale optimization algorithm (WOA) and genetic algorithm (GA) with RF, to make landslide susceptibility mapping for the Ankang City of Shaanxi Province, China. …”
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Distributed Tracking-ADMM Approach for Chance-Constrained Energy Management with Stochastic Wind Power by Wenjuan Li, Yungang Liu, Huijun Liang, Yongchao Man, Fengzhong Li

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Dynamic energy consumption monitoring and scheduling for green buildings: A comprehensive approach by Hua Zheng, Pengming Wang

“…Traditional green building energy efficiency management methods lack real-time optimization and intelligent management and lack effective coordination between systems, resulting in energy waste and limited building energy efficiency optimization effects. …”
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Research on Simultaneous Localization and Intrusion Detection Methodology for Intelligent Trains Based on Multisource Fusion by ZENG Xiang, JIANG Guotao, LYU Yu, LI Cheng, PAN Wenbo, LUO Ziqi

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Dynamic pricing strategy of low-carbon integrated energy system considering multiple uncertainties by BIAN Xinyi, FAN Hong, ZENG Bo

“…In order to further improve the economy and low carbon of the integrated energy system, the paper constructs the structure of the integrated energy system (IES), improves and adds carbon capture devices and electric-to-gas devices in the system, and considers the optimization mechanism with stepped carbon trading to further control carbon emissions. …”
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A hybrid deep learning-based intrusion detection system for EV and UAV charging stations by Rosebell Paul, Mercy Paul Selvan

“…The SS-ADRNN model incorporates squirrel search optimization, which is inspired by the foraging behaviour of squirrels, to dynamically adjust charging station operations based on environmental conditions and demand patterns. …”
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An Interpretable Method for Anomaly Detection in Multivariate Time Series Predictions by Shijie Tang, Yong Ding, Huiyong Wang

“…Anomaly detection methods for industrial control networks using multivariate time series usually adopt deep learning-based prediction models. …”
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Defense Methods for Adversarial Attacks Against Power CPS Data-Driven Algorithms by Weiping ZHU, Yi TANG, Xingshen WEI, Zengji LIU

“…In response to the potential adversarial attacks on data-driven algorithms in power CPS, this paper proposes corresponding defense methods from such three aspects as abnormal data filtering and recovery, algorithm vulnerability mining and optimization, and algorithm self interpretability improvement: abnormal data filter, GAN-based vulnerability mining and optimization method, data knowledge fusion model and its training method. …”
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Analysis on Location Accuracy for the Binocular Stereo Vision System by Lu Yang, Baoqing Wang, Ronghui Zhang, Haibo Zhou, Rongben Wang

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Research on Annual Performance Factor of Water-water Heat Pump System by 杨昭, 赵海波, 胡云峰, 吴坤

“…The annual performance factor(APF) optimization of water-water heat pump was presented.Based on the building load in a whole year,the APF of a heat pump was defined and used as the optimization function,with the area ratio of heat exchanger as the optimization variable.The optimization mathematical models for the on-off control scheme were set up to calculate the APF to study the optimal design and matching between different components.Comparison with different optimization designs with HSPF,SEER,and EER,the APF optimization is nearer to the reality.…”
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The regulation scheme of a double-rotor wind turbine during operation based on the transmission modes of rotors by Yaru Yang, Shaokang Zhang, Yuanyuan Deng, Jing Yuan, Yongxu Hu

“…Addressing the specific control challenges during operation, this study first establishes a geometric model of the Counter-rotating Double-Rotor Wind Turbine (C-DRWT) and an integrated drivetrain model from the dual rotors to the gearbox. …”
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Greening concept in inventory system for deteriorating items with preservation investment and price and stock dependent demand via marine predators algorithm by Hachen Ali, Gobinda Chandra Panda, Adel Fahad Alrasheedi, Ali Akbar Shaikh, Jeonghwan Gwak

“…To solve it efficiently, this study employs the Marine Predators Algorithm (MPA)—a newly developed metaheuristic algorithm well-suited for continuous, nonlinear optimization. Model authenticity is established through a combination of sensitivity analysis, convergence behavior examination, and validation against benchmark test problems from existing literature. …”
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Fatigue Load Prediction of Wind Turbine Drive Train Based on CNN-BiLSTM by Xiaodong WANG, Qing LI, Deyi FU, Yingming LIU, Ruojin WANG

“…This paper addresses the significant deviations observed in traditional fatigue load quantification models employed for control strategies and parameter optimization in operational wind turbines. …”
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Privacy-Preserving Glycemic Management in Type 1 Diabetes: Development and Validation of a Multiobjective Federated Reinforcement Learning Framework by Fatemeh Sarani Rad, Juan Li

“…By integrating federated RL, this framework eliminates hypoglycemia, improves TIR, and preserves data privacy by decentralizing model training. Unlike traditional centralized approaches that require sharing sensitive health data, PRIMO-FRL leverages federated learning to keep patient data local, significantly reducing privacy risks while enabling adaptive and personalized glucose control. …”
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