Physical habitat simulations of the Dal River in Korea using the GEP Model
Created by W.Langdon from
gp-bibliography.bib Revision:1.8129
- @Article{Choi:2015:EE,
-
author = "Byungwoong Choi and Sung-Uk Choi",
-
title = "Physical habitat simulations of the Dal River in Korea
using the {GEP} Model",
-
journal = "Ecological Engineering",
-
volume = "83",
-
pages = "456--465",
-
year = "2015",
-
ISSN = "0925-8574",
-
DOI = "doi:10.1016/j.ecoleng.2015.06.042",
-
URL = "http://www.sciencedirect.com/science/article/pii/S0925857415301038",
-
abstract = "The GEP model, a recently-developed robust artificial
intelligence technique, captures the benefits of both
genetic algorithm and genetic programming by using
chromosomes and expression trees. This paper presents a
physical habitat simulation using the GEP model. The
study area is a 2.5 km long reach of a stream, located
downstream from a dam in the Dal River in Korea. Field
monitoring revealed that Zacco platypus is the dominant
species in the study area. The CCHE2D model and the GEP
model were used for hydraulic and habitat simulations,
respectively. Since the GEP model belongs to the
data-driven approach, the model directly predicts the
composite suitability index using the monitoring data.
The GEP model is capable of considering correlations
between all physical habitat variables, which is a
clear advantage over knowledge-based models, such as
the habitat suitability index model. The model was
first validated using measured data. Distributions of
the composite suitability index were then predicted
using the GEP model for various flows. The predicted
results were compared with those obtained using the
habitat suitability index model. A sensitivity study of
the GEP model was also carried out. Finally, the GEP
model was used to construct habitat suitability curves
for each physical habitat variable. The resulting
habitat suitability curves were found to be very
similar to those constructed by the method of Gosse
(1982). The findings indicate that the conventional
multiplicative aggregation method consistently
underestimates the composite suitability index. Thus,
the geometric mean method is proposed for use with
calibrated coefficients.",
-
keywords = "genetic algorithms, genetic programming, Physical
habitat simulation, GEP model, Habitat suitability
index, Composite suitability index, The Dal River",
- }
Genetic Programming entries for
Byungwoong Choi
Sung-Uk Choi
Citations