Monthly rainfall forecasting by a hybrid neural network of discrete wavelet transformation and deep learning
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DOI: 10.1007/s11269-022-03218-w
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Cited by:
- Prabal Das & D. A. Sachindra & Kironmala Chanda, 2022. "Machine Learning-Based Rainfall Forecasting with Multiple Non-Linear Feature Selection Algorithms," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(15), pages 6043-6071, December.
- Mahrouz Nourali, 2023. "Improved Treatment of Model Prediction Uncertainty: Estimating Rainfall using Discrete Wavelet Transform and Principal Component Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(11), pages 4211-4231, September.
- Guo-Yu Huang & Chi-Ju Lai & Ping-Feng Pai, 2022. "Forecasting Hourly Intermittent Rainfall by Deep Belief Networks with Simple Exponential Smoothing," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(13), pages 5207-5223, October.
- Goksu Tuysuzoglu & Kokten Ulas Birant & Derya Birant, 2023. "Rainfall Prediction Using an Ensemble Machine Learning Model Based on K-Stars," Sustainability, MDPI, vol. 15(7), pages 1-24, March.
- Peiqiang Gao & Wenfeng Du & Qingwen Lei & Juezhi Li & Shuaiji Zhang & Ning Li, 2023. "NDVI Forecasting Model Based on the Combination of Time Series Decomposition and CNN – LSTM," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(4), pages 1481-1497, March.
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Keywords
Monthly rainfall forecasting; Discrete wavelet transform; Long-short term memory; Dilated causal convolution;All these keywords.
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