Neural networks for wave forecasting

By M. C. Deo, A. Jha, A. S. Chaphekar, K. Ravikant. 2001

302 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering, Environmental Engineering, Oceanography

View Paper: https://www.semanticscholar.org/paper/f69d0db69d973d6251402b74cf02dcda9d9221e9

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Electrical and Electronic Engineering

1. Frank E. Curtis

In Environmental Engineering

1. Katya Scheinberg

Citations in the corpus

• A fuzzy inference system for wind-wave modeling (2009, methodology): “…forecasts involved the classical time-series approach, employing stochastic ARMA or ARIMA models (Agrawal and Deo, 2002) or the development of artificial neural networks (ANNs) (Deo and Kiran Kumar, 2000; Deo et al., 2001; Makarynskyy, 2004; Rao and Mandal, 2005; Jain and Deo, 2007).”
• Optimization Methods for Supervised Machine Learning: From Linear Models to Deep Learning (2017, background): “…helped to train DNNs for large-scale applications, such as for speech recognition [40, 35], image classification [18, 47, 77], human action recognition [43], video classification [45], forecasting [56, 36, 81, 83], machine translation [17, 2], and civil engineering [26, 1, 46, 24]; see also [89].”