ArticleScientific reports2025
Accurate AQI forecasting in a high-altitude city using a simulated CVOCA-BiLSTM hybrid model: a case study of Lhasa, Tibet.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Forecasting of the Air Quality Index (AQI) in high-altitude cities is significantly challenged by nonlinear temporal dynamics, particularly due to complex interactions between atmospheric physics and pollutant transport. A hybrid forecasting model integrating a simulated Complex-Valued Optical Convolution Accelerator (CVOCA) with a Bidirectional Long Short-Term Memory (BiLSTM) network is presented to improve prediction accuracy and computational efficiency. The simulated CVOCA module enables high-speed, complex-valued convolution to extract amplitude and phase features from high-dimensional AQI sequences, while the BiLSTM component captures bidirectional temporal dependencies. Performance was evaluated using daily AQI data from Lhasa (2014-2024, 4018 samples). The hybrid model achieved RMSE = 1.60, MAE = 0.93, MAPE = 1.60%, R = 0.997, and R
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