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Ming-Jian Zeng

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Open access Aug 2026

Deep learning-based prediction of negative air ion concentrations using TCN-attention and meteo-temporal fusion transformer

The concentration of negative air ions (NAI) is a key indicator used for evaluating air quality and quantifying the health benefits that forest ecosystems provide. Accurate prediction of NAI concentration holds significant value for ecological tourism planning as well as public health service improvement. However, ex...

Gu Zhang, Ming-Jian Zeng, Wenwen Ai et al. · 0 citations
Open access Sep 2026

An Integrated Multi‐Component Error Verification Method for Numerical Weather Prediction

Errors in weather forecasts remain a critical challenge for high‐resolution numerical weather prediction (NWP) and artificial intelligence forecast models. Traditional verification approaches, such as Threat Score (TS) and Equitable Threat Score (ETS), suffer from “double penalty” issues due to spatial‐temporal misma...

Xiyu Mu, Qi Xu, Guoqing Liu et al. · 0 citations
Open access Jul 2026

Physics-Guided Deep Learning for Short-Term Offshore Wind Power Forecasting

Given wind energy’s growing significance in the world’s energy structure, the demand for high-precision forecasting is more urgent than ever. However, wind power’s inherent non-stationarity is linked to complex and variable meteorological conditions, which pose significant challenges for accurate forecasting. The accur...

Boni Wang, Ming-Jian Zeng, H. Shan et al. · 0 citations

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