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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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Chengjiang Zhou, Ling Xing, Yunhua Jia, Shuyi Wan and Zixuan Zhou
Aiming at the problem that fault feature extraction is susceptible to background noises and burrs, we proposed a new feature extraction method based on a new decomposition method and an effective intrinsic mode function (IMF) selection method. Firstly, p...
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Manish Kumar Pandey, Anu Saini, Karthikeyan Subbiah, Nalini Chintalapudi and Gopi Battineni
Globally, smart cities, infrastructure, and transportation have led to a rise in vehicle numbers, resulting in an increasing number of problems. This includes problems such as air pollution, noise pollution, high energy consumption, and people?s health. ...
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Ziqi Peng, Hongzi Bai, Tatsuo Shiina, Jianglong Deng, Bei Liu and Xian Zhang
LED (light-emitting diode)-lidar (light detection and ranging) has gradually been focused on by researchers because of its characteristics of low power, high stability, and safety to human eyes. However, LED-lidar systems are easily disturbed by backgrou...
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Ahmad Mohsenimanesh, Evgueniy Entchev and Filip Bosnjak
Forecasting the aggregate charging load of a fleet of electric vehicles (EVs) plays an important role in the energy management of the future power system. Therefore, accurate charging load forecasting is necessary for reliable and efficient power system ...
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