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Haoyu Lin, Pengkun Quan, Zhuo Liang, Dongbo Wei and Shichun Di
With the rise of electric vehicles, autonomous driving, and valet parking technologies, considerable research has been dedicated to automatic charging solutions. While the current focus lies on charging robot design and the visual positioning of charging...
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Yan Chen and Chunchun Hu
Accurate prediction of fine particulate matter (PM2.5) concentration is crucial for improving environmental conditions and effectively controlling air pollution. However, some existing studies could ignore the nonlinearity and spatial correlation of time...
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Chi Han, Wei Xiong and Ronghuan Yu
Mega-constellation network traffic forecasting provides key information for routing and resource allocation, which is of great significance to the performance of satellite networks. However, due to the self-similarity and long-range dependence (LRD) of m...
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Hexiang Zheng, Hongfei Hou, Ruiping Li and Changfu Tong
To accurately forecast the future development trend of vegetation in dry areas, it is crucial to continuously monitor phenology, vegetation health indices, and vegetation drought indices over an extended period. This is because drought caused by high tem...
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Xinyu Tian, Qinghe Zheng, Zhiguo Yu, Mingqiang Yang, Yao Ding, Abdussalam Elhanashi, Sergio Saponara and Kidiyo Kpalma
At present, the design of modern vehicles requires improving driving performance while meeting emission standards, leading to increasingly complex power systems. In autonomous driving systems, accurate, real-time vehicle speed prediction is one of the ke...
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Miaomiao Yu, Hongyong Yuan, Kaiyuan Li and Lizheng Deng
To separate the noise and important signal features of the indoor carbon dioxide (CO2) concentration signal, we proposed a noise cancellation method, based on time-varying, filtering-based empirical mode decomposition (TVF-EMD) with Bayesian optimization...
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Tao Zhang, Xiaojun Wang, Zhifeng Jin, Shamsuddin Shahid and Bo Bi
In this paper, the quantitative effects of climatic factor changes on irrigation water use were analyzed in Jiangsu Province from 2004 to 2020 using the Empirical Mode Decomposition (EMD) time-series analysis method. In general, the irrigation water use,...
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Chunyao Hou, Yilun Wei, Hongyi Zhang, Xuezhou Zhu, Dawen Tan, Yi Zhou and Yu Hu
In response to the challenge of limited model availability for predicting the lifespan of super-high arch dams, a hybrid model named EMD-PSO-GPR (EPR) is proposed in this study. The EPR model leverages Empirical Mode Decomposition (EMD), Gaussian Process...
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Asha Jayasree, Santhosh Kumar Sasidharan, Rishidas Sivadas and Jayan A. Ramakrishnan
Rainfall forecasting is critical for the economy, but it has proven difficult due to the uncertainties, complexities, and interdependencies that exist in climatic systems. An efficient rainfall forecasting model will be beneficial in implementing suitabl...
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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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