期刊
ECOLOGICAL INFORMATICS
卷 37, 期 -, 页码 52-58出版社
ELSEVIER
DOI: 10.1016/j.ecoinf.2016.11.012
关键词
Artificial neural network; Ensemble; Stability; Model fit; Poyang
类别
资金
- Major Water Resources Science and Technology Program of Jiangxi Water Resources Department [KT201406]
- Model Development Project for Aquatic Ecology of Lake Poyang
Artificial neural network (ANN) models have been widely used in environmental modeling with considerable success. To improve the reliability of ANN models, ensemble simulations were applied in this study to develop four ANN ensemble models for chlorophyll a simulation in the largest freshwater lake (Lake Poyang) in China. Reliability (evaluated by model fit and stability) of these ANN ensemble models was compared with that of single ANN models from ensemble members. The model fit of these single ANN models varied significantly over repeated runs, indicating the unstable performance of the single ANN models. Comparing with the single ANN models, the ANN ensemble models showed a better model fit and stability, implying the potential of ensemble simulation in achieving a more reliable model. An ensemble size of 30 was adequate for the ANN ensemble models to achieve a good model fit, while an ensemble size of 50 was adequate to achieve good stability. This case study highlighted both the necessity and potential of the ensemble simulation approach to achieve a reliable ANN model with good model fit and stability. (C) 2016 Elsevier B.V. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据