Comparative Study of SVMs and ANNs in Aquifer Water Level Prediction-Reference-Cited by-同舟云学术

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Comparative Study of SVMs and ANNs in Aquifer Water Level Prediction

Published:2010-09 Issue:5 Volume:24 Page:408-413
ISSN:0887-3801
Container-title:Journal of Computing in Civil Engineering
language:en
Short-container-title:J. Comput. Civ. Eng.

Author:

Behzad Mohsen¹²³,Asghari Keyvan¹²³,Coppola Emery A.¹²³

Affiliation:

1. Graduate Student, Dept. of Civil Engineering, Isfahan Univ. of Technology (IUT), 8415683111 Isfahan, Iran (corresponding author).

2. Assistant Professor, Dept. of Civil Engineering, Isfahan Univ. of Technology (IUT), 8415683111 Isfahan, Iran.

3. President, NOAH, L.L.C., 610 Lawrence Rd., Lawrenceville, NJ 08648-4208.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Computer Science Applications,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29CP.1943-5487.0000043

Reference26 articles.

1. Support vector machines for nonlinear state space reconstruction: Application to the Great Salt Lake time series

2. Multi-time scale stream flow predictions: The support vector machines approach

3. Support vector machines (SVMs) for monitoring network design

4. Support vectors-based groundwater head observation networks design

5. Generalization performance of support vector machines and neural networks in runoff modeling

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