Uncovering The Driving Factors Behind Algal Growth In The South-to-north Water Diversion Project Using Advanced Ai

A cross-national team of researchers from China, Germany and The Netherlands developed a deep learning-based Transformer model, Bloomformer-1, designed for end-to-end identification of algal growth driving factors. The model was tested on the Middle Route of the South-to-North Water Diversion Project (MRP) in China and compared to four traditional machine learning models, with the highest R2 (0.80 to 0.94) and lowest RMSE (0.22 to 0.43 μg/L). Bloomformer-1 employs the multi-head-self-attention mechanism, which compares each token to all other tokens in the input sequence.