Physical habitat simulations of the Dal River in Korea using the GEP Model

Byungwoong Choi, Sung-Uk Choi

Research output: Contribution to journalArticle

11 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)456-465
Number of pages10
JournalEcological Engineering
Volume83
DOIs
Publication statusPublished - 2015 Oct 1

Fingerprint

Rivers
habitat
river
simulation
Composite materials
Genetic programming
artificial intelligence
Monitoring
Chromosomes
genetic algorithm
Dams
Artificial intelligence
chromosome
Agglomeration
Genetic algorithms
dam
Hydraulics
index
hydraulics

All Science Journal Classification (ASJC) codes

  • Environmental Engineering
  • Nature and Landscape Conservation
  • Management, Monitoring, Policy and Law

Cite this

@article{5c2be6b5ba79462eb22e95c1ca2e8882,
title = "Physical habitat simulations of the Dal River in Korea using the GEP Model",
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.",
author = "Byungwoong Choi and Sung-Uk Choi",
year = "2015",
month = "10",
day = "1",
doi = "10.1016/j.ecoleng.2015.06.042",
language = "English",
volume = "83",
pages = "456--465",
journal = "Ecological Engineering",
issn = "0925-8574",
publisher = "Elsevier",

}

Physical habitat simulations of the Dal River in Korea using the GEP Model. / Choi, Byungwoong; Choi, Sung-Uk.

In: Ecological Engineering, Vol. 83, 01.10.2015, p. 456-465.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Physical habitat simulations of the Dal River in Korea using the GEP Model

AU - Choi, Byungwoong

AU - Choi, Sung-Uk

PY - 2015/10/1

Y1 - 2015/10/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84938778360&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84938778360&partnerID=8YFLogxK

U2 - 10.1016/j.ecoleng.2015.06.042

DO - 10.1016/j.ecoleng.2015.06.042

M3 - Article

VL - 83

SP - 456

EP - 465

JO - Ecological Engineering

JF - Ecological Engineering

SN - 0925-8574

ER -