Wavelet transform application for/in non-stationary time-series analysis: A review

M Rhif, A Ben Abbes, IR Farah, B Martínez, Y Sang - Applied Sciences, 2019 - mdpi.com
Non-stationary time series (TS) analysis has gained an explosive interest over the recent
decades in different applied sciences. In fact, several decomposition methods were …

Artificial intelligence based models for stream-flow forecasting: 2000–2015

ZM Yaseen, A El-Shafie, O Jaafar, HA Afan, KN Sayl - Journal of Hydrology, 2015 - Elsevier
Summary The use of Artificial Intelligence (AI) has increased since the middle of the 20th
century as seen in its application in a wide range of engineering and science problems. The …

Artificial intelligence-based single and hybrid models for prediction of water quality in rivers: A review

T Rajaee, S Khani, M Ravansalar - Chemometrics and Intelligent …, 2020 - Elsevier
The need for accurate predictions of water quality in rivers has encouraged researchers to
develop new methods and to improve the predictive ability of conventional models. In recent …

Applications of hybrid wavelet–artificial intelligence models in hydrology: a review

V Nourani, AH Baghanam, J Adamowski, O Kisi - Journal of Hydrology, 2014 - Elsevier
Accurate and reliable water resources planning and management to ensure sustainable use
of watershed resources cannot be achieved without precise and reliable models …

A robust method for non-stationary streamflow prediction based on improved EMD-SVM model

E Meng, S Huang, Q Huang, W Fang, L Wu, L Wang - Journal of hydrology, 2019 - Elsevier
Monthly streamflow prediction can offer important information for optimal management of
water resources, flood mitigation, and drought warning. The semi-humid and semi-arid Wei …

Forecasting of groundwater level fluctuations using ensemble hybrid multi-wavelet neural network-based models

R Barzegar, E Fijani, AA Moghaddam… - Science of the Total …, 2017 - Elsevier
Accurate prediction of groundwater level (GWL) fluctuations can play an important role in
water resources management. The aims of the research are to evaluate the performance of …

A review on the applications of wavelet transform in hydrology time series analysis

YF Sang - Atmospheric research, 2013 - Elsevier
In this paper, the wavelet transform methods were briefly introduced, and present
researches and applications of them in hydrology were summarized and reviewed from six …

Two hybrid artificial intelligence approaches for modeling rainfall–runoff process

V Nourani, Ö Kisi, M Komasi - Journal of Hydrology, 2011 - Elsevier
The need for accurate modeling of the rainfall–runoff process has grown rapidly in the past
decades. However, considering the high stochastic property of the process, many models …

[HTML][HTML] Rectification of the bias in the wavelet power spectrum

Y Liu, X San Liang… - Journal of Atmospheric and …, 2007 - journals.ametsoc.org
Rectification of the Bias in the Wavelet Power Spectrum in: Journal of Atmospheric and
Oceanic Technology Volume 24 Issue 12 (2007) Jump to Content Jump to Main Navigation …

Using discrete wavelet transforms to analyze trends in streamflow and precipitation in Quebec and Ontario (1954–2008)

D Nalley, J Adamowski, B Khalil - Journal of hydrology, 2012 - Elsevier
This paper aims to detect trends in mean flow and total precipitation data over southern parts
of Quebec and Ontario, Canada. The main purpose of the trend assessment is to find out …