APA (7th ed.) Citation

Huang, S., & Zhou, L. (2025). A Residual-Corrected Hybrid ARIMA–CNN–LSTM Framework for High-Accuracy Tobacco Sales Forecasting in Regulated Markets. International journal of computational intelligence systems, 18(1), 1-25. https://doi.org/10.1007/s44196-025-00930-4

Chicago Style (17th ed.) Citation

Huang, Shiyu, and Lili Zhou. "A Residual-Corrected Hybrid ARIMA–CNN–LSTM Framework for High-Accuracy Tobacco Sales Forecasting in Regulated Markets." International Journal of Computational Intelligence Systems 18, no. 1 (2025): 1-25. https://doi.org/10.1007/s44196-025-00930-4.

MLA (9th ed.) Citation

Huang, Shiyu, and Lili Zhou. "A Residual-Corrected Hybrid ARIMA–CNN–LSTM Framework for High-Accuracy Tobacco Sales Forecasting in Regulated Markets." International Journal of Computational Intelligence Systems, vol. 18, no. 1, 2025, pp. 1-25, https://doi.org/10.1007/s44196-025-00930-4.