Genetic programming approach on evaporation losses and its effect on climate change for Vaipar Basin

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@Article{Kasiviswanathan:2011:IJCSI,

• author = "K. S. Kasiviswanathan and R. Soundhara Raja Pandian and S. Saravanan and Avinash Agarwal",
• title = "Genetic programming approach on evaporation losses and its effect on climate change for Vaipar Basin",
• journal = "International Journal of Computer Science Issues",
• year = "2011",
• volume = "8",
• number = "2",
• pages = "269--274",
• month = sep,
• publisher = "IJCSI Press",
• keywords = "genetic algorithms, genetic programming, climate change, green house effect",
• ISSN = "16940784",
• URL = "http://www.ijcsi.org/papers/IJCSI-8-5-2-269-274.pdf",
• broken = "http://www.doaj.org/doaj?func=openurl\&genre=article\&issn=16940784\&date=2011\&volume=8\&issue=5\&spage=269",
• size = "6 pages",
• abstract = "Climate change is the major problem that every human being is facing over the world. The rise in fossil fuel usage increases the emission of `greenhouse' gases, particularly carbon dioxide continuously into the earth's atmosphere. This causes a rise in the amount of heat from the sun withheld in the earth's atmosphere that would normally radiated back into space. This increase in heat has led to the greenhouse effect, resulting in climate change and rise in temperature along with other climatological parameters directly affects evaporation losses. Accurate modelling and forecasting of these evaporation losses are important for preventing further effects due to climate change. Evaporation is purely non-linear and varying both spatially and temporally. This needs suitable data driven approach to model and should have the ability to take care of all these non-linear behaviour of the system. As such, though there are many empirical and analytical models suggested in the literature for the estimation of evaporation losses, such models should be used with care and caution. Further, difficulties arise in obtaining all the climatological data used in a given analytical or empirical model. Genetic programming (GP) is one such technique applied where the non-linearity exist. GP has the flexible mathematical structure which is capable of identifying the non-linear relationship between input and output data sets. Thus, it is easy to construct 'local' models for estimating evaporation losses. The performance of GP model is compared with Thornthwaite method, and results from the study indicate that the GP model performed better than the Thornthwaite method. Forecasting of meteorological parameters such as temperature, relative humidity and wind velocity has been performed using Markovian chain series analysis subsequently it is used to estimate the future evaporation losses using developed GP model. Finally the effect of possible future climate change on evaporation losses in Pilavakkal reservoir scheme, India has been discussed.",
• bibsource = "OAI-PMH server at www.doaj.org",
• language = "eng",
• oai = "oai:doaj-articles:c4475caf64dedd913ee20c03b88e8b70",

}

Genetic Programming entries for K S Kasiviswanathan R Soundhara Raja Pandian S Saravanan Avinash Agarwal

Citations