Artificial neural network technique for rainfall forecasting applied to the São Paulo region

By M. C. V. Ramírez, Haroldo Fraga de Campos Velho, N. J. Ferreira. 2005

299 citations recorded by the source corpus.

Subfields: Atmospheric Science, Environmental Engineering

View Paper: https://www.semanticscholar.org/paper/096b74e1f0e48dd2ba58285280b07b84d1a19e2b

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In Environmental Engineering

Citations in the corpus

How Much Meteorological Information Is Necessary to Achieve Reliable Accuracy for Rainfall Estimations (2016, methodology): “[24] used an ANN technique for rainfall forecasting applied to the São Paulo region.”
Multiple regression and Artificial Neural Network for long-term rainfall forecasting using large scale climate modes (2013, methodology): “It has also been used for many cases of rainfall forecasting (Hsu et al., 1995; Luk et al., 2001; Mekanik et al., 2011; Ramírez et al., 2005; Toth et al., 2000).”
Prediction of shear strength parameters of soils using artificial neural networks and multivariate regression methods (2012, background): “The (j, k) element of the matrix isPn i¼1 XjiXik; i=1,…,N for a sample of size N (Valverde Ramirez et al., 2005; Tabari et al., 2009).”
Drought forecasting using artificial neural networks and time series of drought indices (2007, methodology): “Hall (1999) applied ANN for rainfall forecasting in Texas, Kuligowski and Barros (1998) – to predict 6-h rainfalls in two drainage basins in Pennsylvania, Luk et al. (2000) – for short-term rainfall forecasting within a flood warning system and Ramirez et al. (2005) – for daily rainfall forecasting.”
Reservoir-system simulation and optimization techniques (2013, background): “…network modeling has greatly assisted river flow or inflow forecasting (El-Shafie et al. 2007; Karunanithi et al. 1994), rainfall forecasting (Ramirez et al. 2005), groundwater flow remediation (Ranjithan et al. 1993), flood forecasting (Chang et al. 2007) and the design of operating…”
Simulation of artificial neural network model for trunk sap flow of Pyrus pyrifolia and its comparison with multiple-linear regression (2009, methodology): “In the ANN model building process, the node numbers in the hidden layer was chosen by trial and error method (Ramirez et al., 2005).”
Probabilistic quantitative precipitation field forecasting using a two-stage spatial model (2008, background): “2004), neural networks (Koizumi 1999; Ramirez et al. 2005), binning techniques (Gahrs et al.”
Wavelet Analysis-Support Vector Machine Coupled Models for Monthly Rainfall Forecasting in Arid Regions (2015, methodology): “…neuro-fuzzy inference system (ANFIS), and support vector machine (SVM) have been applied to rainfall forecasting (French et al. 1992; Valverde Ramírez et al. 2005; Aksoy and Dahamsheh 2008; Dahamsheh and Aksoy 2008; Srivastava et al. 2010; Wu et al. 2010; Moustris et al. 2011; Kashid and…”
ANN and Fuzzy Logic Models for Simulating Event-Based Rainfall-Runoff (2006, methodology): “ANN has also been applied to sediment transport Tayfur 2002b ; streamflow forecasting Wu et al. 2005; Anctil and Rat 2005 ; rainfall forecasting Ramírez et al. 2005; Olsson et al. 2004 ; seepage Tayfur et al. 2005 ; and dispersion Tayfur and Singh 2005 .”