Application of artificial neural network models to the estimation of chlorophyll a concentration in Lake Koyama, Tottori Prefecture, Japan

Koji Sai, Harada Masayoshi, Isao Yoshida, Kazuaki Hiramatsu, Makito Mori

研究成果: ジャーナルへの寄稿記事

抄録

An artificial neural network model with three-layer structure was applied to estimate chlorophyll a concentration in a lake located in Tottori Prefecture, Japan. First, input variables, which resulted in high calibration accuracy, were searched to examine the optimal network structure. The calibration accuracy was highest when input variables were set to TN, TP, DO, water temperature, solar radiation, air temperature, wind velocity, and Wedderburn number. This result means that the model incorporated the relationship between chlorophyll a concentration and the meteorological, hydraulic, and aquatic factors into the network structure. The adaptability of the estimation of chlorophyll a concentration was examined. As a result, chlorophyll a concentration could not be sufficiently estimated. To improve estimation accuracy, the network structure was reconstructed by considering the time history of the variation of the meteorological and water quality data for the previous 24 hours and incorporating such data into the input variables. The result showed that the estimation accuracy was remarkably improved.

元の言語英語
ページ(範囲)405-409
ページ数5
ジャーナルJournal of the Faculty of Agriculture, Kyushu University
52
発行部数2
出版物ステータス出版済み - 10 1 2007

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Neural Networks (Computer)
Lakes
neural networks
Japan
chlorophyll
lakes
Calibration
calibration
Temperature
Water Quality
wind speed
air temperature
solar radiation
fluid mechanics
water temperature
water quality
Air
Radiation
chlorophyll a
Water

All Science Journal Classification (ASJC) codes

  • Biotechnology
  • Agronomy and Crop Science

これを引用

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title = "Application of artificial neural network models to the estimation of chlorophyll a concentration in Lake Koyama, Tottori Prefecture, Japan",
abstract = "An artificial neural network model with three-layer structure was applied to estimate chlorophyll a concentration in a lake located in Tottori Prefecture, Japan. First, input variables, which resulted in high calibration accuracy, were searched to examine the optimal network structure. The calibration accuracy was highest when input variables were set to TN, TP, DO, water temperature, solar radiation, air temperature, wind velocity, and Wedderburn number. This result means that the model incorporated the relationship between chlorophyll a concentration and the meteorological, hydraulic, and aquatic factors into the network structure. The adaptability of the estimation of chlorophyll a concentration was examined. As a result, chlorophyll a concentration could not be sufficiently estimated. To improve estimation accuracy, the network structure was reconstructed by considering the time history of the variation of the meteorological and water quality data for the previous 24 hours and incorporating such data into the input variables. The result showed that the estimation accuracy was remarkably improved.",
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AU - Sai, Koji

AU - Masayoshi, Harada

AU - Yoshida, Isao

AU - Hiramatsu, Kazuaki

AU - Mori, Makito

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