Multilayer perceptron with different training algorithms for streamflow forecasting View Full Text


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Article Info

DATE

2014-03

AUTHORS

P. Hosseinzadeh Talaee

ABSTRACT

Streamflow forecasting has always been a challenging task for water resources engineers and managers. This study applies Multilayer Perceptron (MLP) networks optimized with three training algorithms, including resilient back-propagation (MLP_RP), variable learning rate (MLP_GDX), and Levenberg–Marquardt (MLP_LM), to forecast streamflow in Aspas Watershed, located in Fars province in southwestern Iran. The algorithms were trained and tested using 3 years of data. Antecedent streamflow with 1 day time lag constituted the first input vector, and MLP with this vector, labeled as MLP1 was the first model. Inclusion of streamflow with two, three, and four time lags led to input vectors 2, 3, and 4 which when combined with MLP resulted in MLP2, MLP3, and MLP4, respectively. It was found that the Levenberg–Marquardt algorithm performed best among three types of training algorithms employed for training the MLP models. Generally, the MLP4_LM model yields the best result with a determination coefficient and a root mean square error of 0.93 and 2.6 (m3/s). More... »

PAGES

695-703

References to SciGraph publications

  • 2010-06. Comparison of artificial neural network and combined models in estimating spatial distribution of snow depth and snow water equivalent in Samsami basin of Iran in NEURAL COMPUTING AND APPLICATIONS
  • 2010-07. Estimation of daily pan evaporation using artificial neural network and multivariate non-linear regression in IRRIGATION SCIENCE
  • 2013-08. Multilayer perceptron for reference evapotranspiration estimation in a semiarid region in NEURAL COMPUTING AND APPLICATIONS
  • 2011-03. Predicting Spatial Distribution of Snow Water Equivalent Using Multivariate Non-linear Regression and Computational Intelligence Methods in WATER RESOURCES MANAGEMENT
  • 1978. The Levenberg-Marquardt algorithm: Implementation and theory in NUMERICAL ANALYSIS
  • 2013-10. Artificial neural network–genetic algorithm for estimation of crop evapotranspiration in a semi-arid region of Iran in NEURAL COMPUTING AND APPLICATIONS
  • 2011-01. Comparison of artificial neural network and multivariate linear regression methods for estimation of daily soil temperature in an arid region in METEOROLOGY AND ATMOSPHERIC PHYSICS
  • 2010-09. Daily Outflow Prediction by Multi Layer Perceptron with Logistic Sigmoid and Tangent Sigmoid Activation Functions in WATER RESOURCES MANAGEMENT
  • 1989-12. Approximation by superpositions of a sigmoidal function in MATHEMATICS OF CONTROL, SIGNALS, AND SYSTEMS
  • 2012-01. Intermittent Streamflow Forecasting by Using Several Data Driven Techniques in WATER RESOURCES MANAGEMENT
  • 2013-07. Prediction of monthly discharge volume by different artificial neural network algorithms in semi-arid regions in ARABIAN JOURNAL OF GEOSCIENCES
  • 2007-06. Artificial neural network model for synthetic streamflow generation in WATER RESOURCES MANAGEMENT
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