Review of Applications of Neuro-Wavelet Techniques in Water Flows

The flow of water over land and oceans is governed by the natural process of hydrological cycle and hence it is highly random and complex. An estimation or prediction of behavior of such flows is thus very difficult and requires continuous research with latest tools of analysis and forecasting. The methods adopted for this purpose range from earlier empirical equations and numerical methods to modern data driven techniques which follow advances in computer technology. The latter coupled with progress in neuro-science had given rise to the method of artificial neural networks (ANNs) which has been applied abundantly since late 1980s to carry out system modeling and prediction type of exercises in water resources and ocean engineering. Despite wide spread applications of ANNs issues such as non-linearity, non-homogenity and non-stationarity of given information continue to elude high accuracy in the results and thus have prompted extension of conventional ANNs to their combination with other pre- or post-processing tools. The wavelet neural network or neuro-wavelet transform (NWT) is a recent effort in this regard to accurately model or predict different types of parameters characterizing river or ocean processes. This paper presents a review of applications of NWT in hydrologic and Oceanic modeling.

[1]  Karim C. Abbaspour,et al.  A wavelet-neural network hybrid modelling approach for estimating and predicting river monthly flows , 2013 .

[2]  Makarand Deo,et al.  Neural networks in ocean engineering , 2006 .

[3]  B. Krishna,et al.  Monthly Rainfall Prediction Using Wavelet Neural Network Analysis , 2013, Water Resources Management.

[4]  J. Adamowski.  River flow forecasting using wavelet and cross‐wavelet transform models , 2008 .

[5]  Makarand Deo,et al.  Prediction of Sea Surface Temperature by Combining Numerical and Neural Techniques , 2016 .

[6]  D. Labat,et al.  Rainfall-runoff relations for karstic springs. Part II: Continuous wavelet and discrete orthogonal multiresolution analyses. , 2000 .

[7]  S. R. Bhakar,et al.  Stochastic modelling of monthly rainfall at Kota Region. , 2006 .

[8]  Ozgur Kisi,et al.  Flow prediction by three back propagation techniques using k-fold partitioning of neural network training data , 2005 .

[9]  G. Sahoo,et al.  Flow forecasting for a Hawaii stream using rating curves and neural networks , 2006 .

[10]  Achilleas Zapranis,et al.  Wavelet Neural Networks: A Practical Guide , 2011, Neural Networks.

[11]  Makarand Deo,et al.  Real time wave forecasting using neural networks , 1998 .

[12]  K. P. Sudheer,et al.  A data‐driven algorithm for constructing artificial neural network rainfall‐runoff models , 2002 .

[13]  M. C. Deo,et al.  Neural-Network-Based Data Assimilation to Improve Numerical Ocean Wave Forecast , 2016, IEEE Journal of Oceanic Engineering.

[14]  Yuqiong Liu,et al.  A wavelet-based approach to assessing timing errors in hydrologic predictions , 2011 .

[15]  U. Okkan,et al.  Wavelet neural network model for reservoir inflow prediction , 2012 .

[16]  Mohammed El-Diasty,et al.  Development of wavelet network model for accurate water levels prediction with meteorological effects , 2015 .

[17]  Bellie Sivakumar,et al.  River flow forecasting: use of phase-space reconstruction and artificial neural networks approaches , 2002 .

[18]  Rahul Barman,et al.  A new approach for deriving temperature and salinity fields in the Indian Ocean using artificial neural networks , 2010 .

[19]  M. C. Deo,et al.  Neural networks for wave forecasting , 2001 .

[20]  V. Panchang,et al.  One-Day Wave Forecasts Based on Artificial Neural Networks , 2006 .

[21]  N. K. Bose,et al.  Neural Network Fundamentals with Graphs, Algorithms and Applications , 1995 .

[22]  Ozgur Kisi,et al.  Stream flow forecasting using neuro‐wavelet technique , 2008 .

[23]  O. Makarynskyy,et al.  Improving wave predictions with artificial neural networks , 2004 .

[24]  Hikmet Kerem Cigizoglu,et al.  Estimation, forecasting and extrapolation of river flows by artificial neural networks , 2003 .

[25]  H. K. Cigizoglu,et al.  Prediction of daily precipitation using wavelet—neural networks , 2009 .

[26]  O. Kisi.  Neural Networks and Wavelet Conjunction Model for Intermittent Streamflow Forecasting , 2009 .

[27]  Shreenivas Londhe,et al.  Prediction of extreme wave heights using neuro wavelet technique , 2016 .

[28]  K. C. Khare,et al.  Wave forecasts using wind information and genetic programming , 2012 .

[29]  P. C. Pandey,et al.  Tsunami travel time prediction using neural networks , 2006 .

[30]  Paul S. Addison,et al.  Wavelet Transform Analysis of Open Channel Wake Flows , 2001 .

[31]  S. Mallat.  VI – Wavelet zoom , 1999 .

[32]  T. Rientjes,et al.  Constraints of artificial neural networks for rainfall-runoff modelling: trade-offs in hydrological state representation and model evaluation , 2005 .

[33]  Vahid Nourani,et al.  Forecasting Daily Precipitation Using Hybrid Model of Wavelet-Artificial Neural Network and Comparison with Adaptive Neurofuzzy Inference System (Case Study: Verayneh Station, Nahavand) , 2014 .

[34]  Paresh Chandra Deka,et al.  Discrete wavelet neural network approach in significant wave height forecasting for multistep lead time , 2012 .

[35]  Pradnya Dixit,et al.  Removing prediction lag in wave height forecasting using Neuro - Wavelet modeling technique , 2015 .

[36]  Yogesh H. Dandawate,et al.  Wave Forecasting Using Neuro Wavelet Technique , 2014 .

[37]  Ozgur Kisi,et al.  Precipitation Forecasting Using Wavelet-Genetic Programming and Wavelet-Neuro-Fuzzy Conjunction Models , 2011 .

[38]  Ahmadreza Zamani,et al.  Learning from data for wind–wave forecasting , 2008 .

[39]  K. P. Moustris,et al.  Precipitation Forecast Using Artificial Neural Networks in Specific Regions of Greece , 2011 .

[40]  Mehmet Özger,et al.  Significant wave height forecasting using wavelet fuzzy logic approach , 2010 .

[41]  S. Mandal,et al.  Ocean wave forecasting using recurrent neural networks , 2006 .

[42]  S. Jain,et al.  Radial Basis Function Neural Network for Modeling Rating Curves , 2003 .

[43]  Felice Arena,et al.  The Reconstruction of Significant Wave Height Time Series by Using a Neural Network Approach , 2004 .

[44]  Yan-Fang Sang,et al.  A review on the applications of wavelet transform in hydrology time series analysis , 2013 .