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

WenJun Zhang, ChangJun Bai and GuoDao Liu

Ecological Modelling, 2007, vol. 201, issue 3, 317-325

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.

Keywords: Neural networks; Elman network; Linear network; Differential equation; Modeling; Ecosystem; Cabbage (search for similar items in EconPapers)
Date: 2007
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:201:y:2007:i:3:p:317-325

DOI: 10.1016/j.ecolmodel.2006.09.022

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