Hybrid Wavelet Neural Network Approach for Daily Inflow Forecasting Using Tropical Rainfall Measuring Mission Data-Reference-Cited by-同舟云学术

Hybrid Wavelet Neural Network Approach for Daily Inflow Forecasting Using Tropical Rainfall Measuring Mission Data

Published:2019-02 Issue:2 Volume:24 Page:04018062
ISSN:1084-0699
Container-title:Journal of Hydrologic Engineering
language:en
Short-container-title:J. Hydrol. Eng.

Author:

Santos Celso A. G.¹,Freire Paula K. M. M.²,Silva Richarde M. da³,Akrami Seyed A.⁴

Affiliation:

1. Professor, Dept. of Civil and Environmental Engineering, Federal Univ. of Paraíba, 58051-900 João Pessoa, Paraíba, Brazil (corresponding author).

2. Ph.D. Student, Dept. of Civil and Environmental Engineering, Federal Univ. of Paraíba, 58051-900 João Pessoa, Paraíba, Brazil.

3. Associate Professor, Dept. of Geosciences, Federal Univ. of Paraíba, 58051-900 João Pessoa, Paraíba, Brazil.

4. Head of Research Division, Tabriz Heritage Enterprise Hentian Kajang, Jalan Reko, 43000 Kajang, Selangore, Malaysia; Dept. of Civil and Structural Engineering, Universiti Kebangsaan Malaysia, 43600 UKM, Bangi Selangor, Malaysia.

Publisher

American Society of Civil Engineers (ASCE)

Subject

General Environmental Science,Water Science and Technology,Civil and Structural Engineering,Environmental Chemistry

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29HE.1943-5584.0001725

Reference37 articles.

1. Development of a coupled wavelet transform and neural network method for flow forecasting of non-perennial rivers in semi-arid watersheds

2. Rainfall data analyzing using moving average (MA) model and wavelet multi-resolution intelligent model for noise evaluation to improve the forecasting accuracy

3. Calibrating hourly rainfall-runoff models with daily forcings for streamflow forecasting applications in meso-scale catchments

4. An autonomous decision support system for manganese forecasting in subtropical water reservoirs

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