Prediction of algal blooms using genetic programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8051
- @Article{Sivapragasam20101849,
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author = "C. Sivapragasam and Nitin Muttil and S. Muthukumar and
V. M. Arun",
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title = "Prediction of algal blooms using genetic programming",
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journal = "Marine Pollution Bulletin",
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volume = "60",
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number = "10",
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pages = "1849--1855",
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year = "2010",
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keywords = "genetic algorithms, genetic programming, Mathematical
modelling, Harmful algal bloom",
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publisher = "Elsevier",
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ISSN = "0025-326X",
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URL = "https://vuir.vu.edu.au/15835/",
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URL = "http://www.sciencedirect.com/science/article/B6V6N-50F9603-1/2/b3bd8078447bc4206918e5d0eaebc0ef",
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DOI = "doi:10.1016/j.marpolbul.2010.05.020",
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abstract = "In this study, an attempt was made to mathematically
model and predict algal blooms in Tolo Harbor (Hong
Kong) using genetic programming (GP). Chlorophyll plays
a vital role in blooms and was used in this model as a
measure of algal bloom biomass, and eight other
variables were used as input for its prediction. It has
been observed that GP evolves multiple models with
almost the same values of errors-of-measure. Previous
studies on GP modeling have primarily focused on
comparing GP results with actual values. In contrast,
in this study, the main aim was to propose a systematic
procedure for identifying the most appropriate GP model
from a list of feasible models (with similar
error-of-measure) using a physical understanding of the
process aided by data interpretation. Evaluation of the
GP-evolved equations shows that they correctly identify
the ecologically significant variables. Analysis of the
final GP-evolved mathematical model indicates that, of
the eight variables assumed to affect algal blooms, the
most significant effects are due to chlorophyll, total
inorganic nitrogen and dissolved oxygen for a 1-week
prediction. For longer lead predictions (biweekly),
secchi-disc depth and temperature appear to be
significant variables, in addition to chlorophyll.",
- }
Genetic Programming entries for
C Sivapragasam
Nitin Muttil
S Muthukumar
V M Arun
Citations