REAL-TIME PREDICTION OF CHLOROPHYLL-ATIME SERIES IN A EUTROPHIC AGRICULTURAL RESERVOIR IN A COASTAL ZONE USING RECURRENT NEURAL NETWORKS WITH PERIODIC CHAOS NEURONS

Author:

Harada Masayoshi1,Tominaga Takafumi2,Hiramatsu Kazuaki1,Marui Atsushi3

Affiliation:

1. Department of Agro-Environmental Sciences, Faculty of Agriculture; Kyushu University; Higashi-ku Fukuoka Japan

2. Kyushu Electric Power Co., Inc.; Chuou-ku Fukuoka Japan

3. Faculty of Agriculture and Life Science; Hirosaki University; Bunkyo-cho Hirosaki Japan

Publisher

Wiley

Subject

Soil Science,Agronomy and Crop Science

Reference27 articles.

1. Chaotic neural networks;Aihara;Physics Letters A,1990

2. A fluorometric method for the differentiation of algal populations in vivo and in situ;Beutler;Photosynthesis Research,2002

3. Artificial neural network modelling of concentrations of nitrogen, phosphorus and dissolved oxygen in a non-point source polluted river in Zhejiang Province, southeast China;Chen;Hydrological Processes,2010

4. Prediction of contamination potential of groundwater arsenic in Cambodia, Laos, and Thailand using artificial neural network;Cho;Water Research,2011

5. Short-term forecasting of dissolved oxygen in eutrophic lake with real-time data by local approximation;Harada;Journal of Rainwater Catchment Systems,2005

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