Application of a simple genetic algorithm for the calibration of aquatic ecosystem model of an agricultural pond

Nguyen Do Thuy, Harada Masayoshi, Kazuaki Hiramatsu, Shinji Fukuda

研究成果: ジャーナルへの寄稿記事

抄録

In this study, we aim to construct and apply a simple genetic algorithm (SGA) to optimize a large number of parameters of an one-box ecosystem model. The ecosystem model was used to simulate the water quality over a 6-month period based on the new observation data in an agricultural pond which was strongly influenced by a green algal bloom. Of the 54 parameters in this model, 10 important parameters were initially selected for the optimization, with one other parameter being subsequently added. The SGA program was used for three purposes, namely (1) to narrow the search space for the 10 parameters, (2) to assess the influence of the additional parameter on the optimization results, and (3) to observe the distribution and convergence of the optimized values for the 10 selected parameters. In the next step, new ranges for these 10 important parameters were assigned and the SGA was applied to all 54 model parameters to seek the optimum value for each parameter. The modeling approach and the results presented here provide valuable and reliable evidences of the optimum parameters for further simulations to clarify the mechanisms of the biochemical processes in the water.

元の言語英語
ページ(範囲)1-15
ページ数15
ジャーナルPaddy and Water Environment
12
発行部数1
DOI
出版物ステータス出版済み - 1 1 2014

Fingerprint

Aquatic ecosystems
Ponds
genetic algorithm
aquatic ecosystem
calibration
pond
Genetic algorithms
Calibration
Ecosystems
agricultural statistics
biochemical mechanisms
ecosystems
Water quality
algal blooms
water quality
parameter
aquatic ecosystems
Water
ecosystem
water

All Science Journal Classification (ASJC) codes

  • Environmental Engineering
  • Water Science and Technology
  • Agronomy and Crop Science

これを引用

Application of a simple genetic algorithm for the calibration of aquatic ecosystem model of an agricultural pond. / Do Thuy, Nguyen; Masayoshi, Harada; Hiramatsu, Kazuaki; Fukuda, Shinji.

:: Paddy and Water Environment, 巻 12, 番号 1, 01.01.2014, p. 1-15.

研究成果: ジャーナルへの寄稿記事

@article{b07ddef3edf84a56828aba9978be27c6,
title = "Application of a simple genetic algorithm for the calibration of aquatic ecosystem model of an agricultural pond",
abstract = "In this study, we aim to construct and apply a simple genetic algorithm (SGA) to optimize a large number of parameters of an one-box ecosystem model. The ecosystem model was used to simulate the water quality over a 6-month period based on the new observation data in an agricultural pond which was strongly influenced by a green algal bloom. Of the 54 parameters in this model, 10 important parameters were initially selected for the optimization, with one other parameter being subsequently added. The SGA program was used for three purposes, namely (1) to narrow the search space for the 10 parameters, (2) to assess the influence of the additional parameter on the optimization results, and (3) to observe the distribution and convergence of the optimized values for the 10 selected parameters. In the next step, new ranges for these 10 important parameters were assigned and the SGA was applied to all 54 model parameters to seek the optimum value for each parameter. The modeling approach and the results presented here provide valuable and reliable evidences of the optimum parameters for further simulations to clarify the mechanisms of the biochemical processes in the water.",
author = "{Do Thuy}, Nguyen and Harada Masayoshi and Kazuaki Hiramatsu and Shinji Fukuda",
year = "2014",
month = "1",
day = "1",
doi = "10.1007/s10333-012-0353-z",
language = "English",
volume = "12",
pages = "1--15",
journal = "Paddy and Water Environment",
issn = "1611-2490",
publisher = "Springer Verlag",
number = "1",

}

TY - JOUR

T1 - Application of a simple genetic algorithm for the calibration of aquatic ecosystem model of an agricultural pond

AU - Do Thuy, Nguyen

AU - Masayoshi, Harada

AU - Hiramatsu, Kazuaki

AU - Fukuda, Shinji

PY - 2014/1/1

Y1 - 2014/1/1

N2 - In this study, we aim to construct and apply a simple genetic algorithm (SGA) to optimize a large number of parameters of an one-box ecosystem model. The ecosystem model was used to simulate the water quality over a 6-month period based on the new observation data in an agricultural pond which was strongly influenced by a green algal bloom. Of the 54 parameters in this model, 10 important parameters were initially selected for the optimization, with one other parameter being subsequently added. The SGA program was used for three purposes, namely (1) to narrow the search space for the 10 parameters, (2) to assess the influence of the additional parameter on the optimization results, and (3) to observe the distribution and convergence of the optimized values for the 10 selected parameters. In the next step, new ranges for these 10 important parameters were assigned and the SGA was applied to all 54 model parameters to seek the optimum value for each parameter. The modeling approach and the results presented here provide valuable and reliable evidences of the optimum parameters for further simulations to clarify the mechanisms of the biochemical processes in the water.

AB - In this study, we aim to construct and apply a simple genetic algorithm (SGA) to optimize a large number of parameters of an one-box ecosystem model. The ecosystem model was used to simulate the water quality over a 6-month period based on the new observation data in an agricultural pond which was strongly influenced by a green algal bloom. Of the 54 parameters in this model, 10 important parameters were initially selected for the optimization, with one other parameter being subsequently added. The SGA program was used for three purposes, namely (1) to narrow the search space for the 10 parameters, (2) to assess the influence of the additional parameter on the optimization results, and (3) to observe the distribution and convergence of the optimized values for the 10 selected parameters. In the next step, new ranges for these 10 important parameters were assigned and the SGA was applied to all 54 model parameters to seek the optimum value for each parameter. The modeling approach and the results presented here provide valuable and reliable evidences of the optimum parameters for further simulations to clarify the mechanisms of the biochemical processes in the water.

UR - http://www.scopus.com/inward/record.url?scp=84892434331&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84892434331&partnerID=8YFLogxK

U2 - 10.1007/s10333-012-0353-z

DO - 10.1007/s10333-012-0353-z

M3 - Article

VL - 12

SP - 1

EP - 15

JO - Paddy and Water Environment

JF - Paddy and Water Environment

SN - 1611-2490

IS - 1

ER -