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Protocol for developing ANN models and its application to the assessment of the quality of the ANN model development process in drinking water quality modelling

机译:人工神经网络模型开发协议及其在饮用水水质模型中对人工神经网络模型开发过程质量评估的应用

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The application of Artificial Neural Networks (ANNs) in the field of environmental and water resources modelling has become increasingly popular since early 1990s. Despite the recognition of the need for a consistent approach to the development of ANN models and the importance of providing adequate details of the model development process, there is no systematic protocol for the development and documentation of ANN models. In order to address this shortcoming, such a protocol is introduced in this paper. In addition, the protocol is used to critically review the quality of the ANN model development and reporting processes employed in 81 journal papers since 2000 in which ANNs have been used for drinking water quality modelling. The results show that model architecture selection is the best implemented step, while greater focus should be given to input selection considering input independence and model validation considering replicative and structural validity.
机译:自1990年代初以来,人工神经网络(ANN)在环境和水资源建模领域的应用已变得越来越流行。尽管认识到需要采用一致的方法来开发ANN模型,并且必须提供模型开发过程的足够详细信息,但尚无用于开发和记录ANN模型的系统协议。为了解决这个缺点,本文引入了这样的协议。此外,自2000年以来,该协议用于严格审查ANN模型开发和报告过程的质量,该论文在81篇期刊论文中采用,其中ANN已用于饮用水水质建模。结果表明,模型体系结构选择是最佳实现步骤,而考虑输入独立性和考虑复制和结构有效性的模型验证应更着重于输入选择。

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