A Genetic Programming Approach to System Identification of Rainfall-Runoff Models
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41330%2F17%3A74734" target="_blank" >RIV/60460709:41330/17:74734 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/s11269-017-1719-1" target="_blank" >http://dx.doi.org/10.1007/s11269-017-1719-1</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s11269-017-1719-1" target="_blank" >10.1007/s11269-017-1719-1</a>
Alternative languages
Result language
angličtina
Original language name
A Genetic Programming Approach to System Identification of Rainfall-Runoff Models
Original language description
Advancements in data acquisition, storage and retrieval are progressing at an extraordinary rate, whereas the same in the field of knowledge extraction from data is yet to be accomplished. The challenges associated with hydrological datasets, including complexity, non-linearity and multicollinearity, motivate the use of machine learning to build hydrological models. Increasing global climate change and urbanization call for better understanding of altered rainfall-runoff processes. There is a requirement that models are intelligible estimates of underlying physics, coupling explanatory and predictive components, maintaining parsimony and accuracy. Genetic Programming, an evolutionary computation technique has been used for short-term prediction and forecast in the field of hydrology. Advancing data science in hydrology can be achieved by tapping the full potential of GP in defining an evolutionary flexible modelling framework that balances prior information, simulation accuracy and strategy for futur
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10501 - Hydrology
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
WATER RESOURCES MANAGEMENT
ISSN
0920-4741
e-ISSN
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Volume of the periodical
31
Issue of the periodical within the volume
12
Country of publishing house
CZ - CZECH REPUBLIC
Number of pages
18
Pages from-to
3975-3992
UT code for WoS article
000407831200017
EID of the result in the Scopus database
2-s2.0-85021845733