Improved Particle Swarm Optimization–Based Artificial Neural Network for Rainfall-Runoff Modeling-Reference-Cited by-同舟云学术

Improved Particle Swarm Optimization–Based Artificial Neural Network for Rainfall-Runoff Modeling

Published:2014-07 Issue:7 Volume:19 Page:1320-1329
ISSN:1084-0699
Container-title:Journal of Hydrologic Engineering
language:en
Short-container-title:J. Hydrol. Eng.

Author:

Asadnia Mohsen¹,Chua Lloyd H. C.²,Qin X. S.²,Talei Amin³

Affiliation:

1. Research Associate, DHI-NTU Water and Environment Research Centre and Education Hub, Nanyang Technological Univ., 50 Nanyang Ave., Singapore 639798.

2. Assistant Professor, School of Civil and Environmental Engineering, Nanyang Technological Univ., 50 Nanyang Ave., Singapore 639798.

3. Lecturer, School of Engineering, Monash Univ., Sunway Campus, Jalan Lagoon Selatan, Bandar Sunway, 46150 Selangor Darul Ehsan, Malaysia (corresponding author).

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.1943-5584.0000927

Reference55 articles.

1. Hybrid discrete PSO with GA operators for efficient QoS-multicast routing

2. Neural Networks for Hydrological Modeling

3. A comparative study of artificial neural networks and neuro-fuzzy in continuous modeling of the daily and hourly behaviour of runoff

4. A counterpropagation fuzzy-neural network modeling approach to real time streamflow prediction

5. Chau K. (2004). “River stage forecasting with particle swarm optimization.” Proc. 17th Int. Conf. on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems IEA/AIE 2004 Springer Berlin Heidelberg Germany 1166–1173.

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