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Haoran Du, Jixin Wang, Wenjun Qian and Xunan Zhang
Variational modal decomposition (VMD) is frequently employed for both signal decomposition and extracting features; however, the decomposition outcome is influenced by the quantity of intrinsic modal functions (IMFs) and the specific parameter values of ...
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Kai Lu, Jing Liang, Mengnan Liu, Zhixiong Lu, Jinzhong Shi, Pengfei Xing and Lin Wang
Transmission efficiency is a key characteristic of Hydro-mechanical Continuously Variable Transmission (HMCVT), which is related to the performance of heavy-duty tractors. Predicting the HMCVT transmission efficiency is beneficial for the real-time adjus...
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Mingfei Wang, Xiangshu Kong, Feifei Shan, Wengang Zheng, Pengfei Ren, Jiaoling Wang, Chunling Chen, Xin Zhang and Chunjiang Zhao
Temperature has a significant impact on the production of edible mushrooms. The industrial production of edible mushrooms is committed to accurately maintaining the temperature inside the mushroom room within a certain range to achieve quality and effici...
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Dacheng Yu, Mingjun Zhang, Feng Yao and Jitao Li
Variational Mode Decomposition (VMD) has typically been used in weak fault feature extraction in recent years. The problem analyzed in this study is weak fault feature extraction and the enhancement of AUV thrusters based on Artificial Rabbits Optimizati...
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Aymane Ahajjam, Jaakko Putkonen, Emmanuel Chukwuemeka, Robert Chance and Timothy J. Pasch
Local weather forecasts in the Arctic outside of settlements are challenging due to the dearth of ground-level observation stations and high computational costs. During winter, these forecasts are critical to help prepare for potentially hazardous weathe...
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Qi Liu, Peng Nie, Hualin Dai, Liyuan Ning and Jiaxing Wang
Convolutional neural networks (CNN) are widely used for structural damage identification. However, the presence of environmental disturbances introduces noise into the acquired acceleration response data, impairing the performance of CNN models. In this ...
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Hongkang Chen, Tieding Lu, Jiahui Huang, Xiaoxing He and Xiwen Sun
Changes in sea level exhibit nonlinearity, nonstationarity, and multivariable characteristics, making traditional time series forecasting methods less effective in producing satisfactory results. To enhance the accuracy of sea level change predictions, t...
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Xuguo Jiao, Daoyuan Zhang, Dongran Song, Dongdong Mu, Yanbing Tian and Haotian Wu
As one of the fastest-growing new energy sources, wind power technology has attracted widespread attention from all over the world. In order to improve the quality of wind power generation, wind speed prediction is an indispensable task. In this paper, a...
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Jin Zhang, Yiqi Huang, Yu Pi, Cheng Sun, Wangyang Cai and Yuanyuan Huang
With the continuous development of the software industry, software is gradually becoming more inclined towards containerized deployment. This paper provides a prediction algorithm based on deep learning to monitor and record the resource usage of the mac...
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Xiaolong Zhou, Xiangkun Wang, Haotian Wang, Linlin Cao, Zhongyuan Xing and Zhilun Yang
Rotor fault diagnosis has attracted much attention due to its difficulties such as non-stationarity of fault signals, difficulty in fault feature extraction and low diagnostic accuracy of small samples. In order to extract fault feature information of ro...
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