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Neural network modeling of ecosystems: A case study on cabbage growth system

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  • Zhang, WenJun
  • Bai, ChangJun
  • Liu, GuoDao

Abstract

A deep understanding on the intrinsic mechanism is required to develop a highly specialized mechanistic model for ecosystem dynamics. However, it is usually hard to do for most of the ecological and environmental problems, because of the lack of a consistent theoretical background. Neural networks are universal and flexible models for linear and non-linear systems. This paper aimed to modeling an ecosystem using neural network models and the conventional model, and assessing their effectiveness in the dynamic simulation of ecosystem. Elman neural network model, linear neural network model, and linear ordinary differential equation were developed to simulate the dynamics of Chinese cabbage growth system recorded in the field. Matlab codes for these neural network models were given. Sensitivity analysis was conducted to detect the robustness of these models.

Suggested Citation

  • Zhang, WenJun & Bai, ChangJun & Liu, GuoDao, 2007. "Neural network modeling of ecosystems: A case study on cabbage growth system," Ecological Modelling, Elsevier, vol. 201(3), pages 317-325.
    • Handle: RePEc:eee:ecomod:v:201:y:2007:i:3:p:317-325
    DOI: 10.1016/j.ecolmodel.2006.09.022
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    References listed on IDEAS

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    1. Sharma, V. & Negi, S. C. & Rudra, R. P. & Yang, S., 2003. "Neural networks for predicting nitrate-nitrogen in drainage water," Agricultural Water Management, Elsevier, vol. 63(3), pages 169-183, December.
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    1. Kelvin López-Aguilar & Adalberto Benavides-Mendoza & Susana González-Morales & Antonio Juárez-Maldonado & Pamela Chiñas-Sánchez & Alvaro Morelos-Moreno, 2020. "Artificial Neural Network Modeling of Greenhouse Tomato Yield and Aerial Dry Matter," Agriculture, MDPI, vol. 10(4), pages 1-14, April.
    2. Zhang, WenJun & Zhang, XiYan, 2008. "Neural network modeling of survival dynamics of holometabolous insects: A case study," Ecological Modelling, Elsevier, vol. 211(3), pages 433-443.
    3. Takeshi Matsunaga, Fabio & Rakocevic, Miroslava & Brancher, Jacques Duílio, 2014. "Modeling the 3D structure and rhythmic growth responses to environment in dioecious yerba-mate," Ecological Modelling, Elsevier, vol. 290(C), pages 34-44.
    4. Varga, M. & Csukas, B., 2017. "Generation of extensible ecosystem models from a network structure and from locally executable programs," Ecological Modelling, Elsevier, vol. 364(C), pages 25-41.

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