Daily Reservoir Runoff Forecasting Method Using Artificial Neural Network Based on Quantum-behaved Particle Swarm Optimization-Reference-Cited by-同舟云学术

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Daily Reservoir Runoff Forecasting Method Using Artificial Neural Network Based on Quantum-behaved Particle Swarm Optimization

Published:2015-07-31 Issue:12 Volume:7 Page:4232-4246
ISSN:2073-4441
Container-title:Water
language:en
Short-container-title:Water

Author:

Cheng Chun-tian,Niu Wen-jing,Feng Zhong-kai,Shen Jian-jian,Chau Kwok-wing

Publisher

MDPI AG

Subject

Water Science and Technology,Aquatic Science,Geography, Planning and Development,Biochemistry

Link

http://www.mdpi.com/2073-4441/7/8/4232/pdf

Reference33 articles.

1. Daily reservoir inflow forecasting combining QPF into ANNs model

2. Comparing Low and High-Level Hybrid Algorithms on the Two-Objective Optimal Design of Water Distribution Systems

3. Effective and efficient global optimization for conceptual rainfall-runoff models

4. Comparison of the ARMA, ARIMA, and the autoregressive artificial neural network models in forecasting the monthly inflow of Dez dam reservoir

5. Evaluation of medium-range runoff forecasts for a 50km2 watershed

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