Genetic Programming for Modelling Long-Term Hydrological Time Series
Created by W.Langdon from
gp-bibliography.bib Revision:1.8028
- @InProceedings{Wang:2009:ICNC,
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author = "Wenchuan Wang and Dongmei Xu and Lin Qiu and
Jianqin Ma",
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title = "Genetic Programming for Modelling Long-Term
Hydrological Time Series",
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booktitle = "Fifth International Conference on Natural Computation,
ICNC '09",
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year = "2009",
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month = aug,
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volume = "4",
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pages = "265--269",
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keywords = "genetic algorithms, genetic programming, artificial
neural network, autocorrelation function, evolutionary
computing method, flow prediction method, hydrological
time series forecasting, lagged input variable, monthly
river flow discharge, reservoir inflow sequence data,
root mean square error, transparent-structured system
identification, channel flow, correlation methods,
forecasting theory, identification, mean square error
methods, neural nets, prediction theory, time series",
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DOI = "doi:10.1109/ICNC.2009.210",
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abstract = "In recent years, artificial neural networks (ANN) have
emerged as a novel identification technique for the
forecasting of hydrological time series. However, they
represent their knowledge in terms of a weight matrix
that is not accessible to human understanding at
present. The purpose of this study is to develop a flow
prediction method, based on the genetic programming
(GP), which is an evolutionary computing method that
provides `transparent' and structured system
identification. In terms of statistical characteristic
of reservoir inflow sequence data, the autocorrelation
function is employed to make certain amount of lagged
input variables and the root mean square error is
adopted as fitness of evaluation. The GP model is
examined using the long-term observations of monthly
river flow discharges. Through the comparison of its
performance with those of the ANN, it is demonstrated
that the GP model is an effective algorithm to forecast
the long-term discharges.",
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notes = "Also known as \cite{5366249}",
- }
Genetic Programming entries for
Wen-Chuan Wang
Dongmei Xu
Lin Qiu
Jianqin Ma
Citations