Prediction of inflows from dam catchment using genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@Article{Atiquzzaman:2016:IJHST,

• title = "Prediction of inflows from dam catchment using genetic programming",
• author = "Md Atiquzzaman and Jaya Kandasamy",
• journal = "International Journal of Hydrology Science and Technology",
• year = "2016",
• month = mar # "~28",
• volume = "6",
• number = "2",
• pages = "103--117",
• keywords = "genetic algorithms, genetic programming, MIKE11-NAM, hydroinformatics, climate scenarios, forecasting, hydrology, rainfall prediction, inflows, inflow prediction, catchment runoff, dam catchment, water management, water resources, Australia, flow simulation",
• publisher = "Inderscience Publishers",
• ISSN = "2042-7816",
• bibsource = "OAI-PMH server at www.inderscience.com",
• language = "eng",
• rights = "Inderscience Copyright",
• URL = "http://www.inderscience.com/link.php?id=75560",
• DOI = "doi:10.1504/IJHST.2016.075560",
• abstract = "Application of hydroinformatics tools for managing water resources is common in the water industry. Over the last few decades, several hydroinformatics tools including genetic programming (GP) have been developed and applied in hydrology. GP has been successfully applied for calibration of numerous event-based rainfall and runoff models. However, applying GP to predict long-term time series for the management of water resources is limited. This study demonstrates GP's application in long-term prediction of catchment runoff concerning a dam located in Oberon, New South Wales, Australia. The calibration showed excellent agreement between the observed and simulated flows recorded over 30 years. The model was then applied for the assessment of catchment yields for a future 100 years flows based on two assumed climatic scenarios.",

}

Genetic Programming entries for Md Atiquzzaman Jaya Kandasamy

Citations