Improving management of windrow composting systems by modeling runoff water quality dynamics using recurrent neural network

Natalia V. Bhattacharjee and Ernest W. Tollner

Ecological Modelling, 2016, vol. 339, issue C, 68-76

Abstract: The recurrent neural network is a tool that can provide valuable insights when forecasting future likelihood of events using dynamic time series. One of the challenging research problems is to extend the black-box modeling into white-box modeling in order to gain insights into the physical processes. Sensitivity analysis has shown a great contribution in overcoming this challenge. The main objective of this study was to perform a detailed sensitivity analysis of recurrent neural network in order to identify parameters that are important for predicting water quality constituents.

Keywords: Sensitivity analysis; Recurrent neural network; Dynamic modeling; Water quality; Runoff; Windrow composting pad (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:339:y:2016:i:c:p:68-76

DOI: 10.1016/j.ecolmodel.2016.08.011

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