Moisture Content Prediction in the Switchgrass (Panicum virgatum) Drying Process Using Artificial Neural Networks
作者： Víctor Martínez-Martínez , Jaime Gomez-Gil , Timothy S. Stombaugh , Michael D. Montross , Javier M. Aguiar
DOI: 10.1080/07373937.2015.1005228
关键词:
摘要: This article proposes two artificial neural network (ANN)-based models to characterize the switchgrass drying process: The first one processes with constant air temperature and relative humidity second variable conditions rainfall. ANN-based proposed estimated moisture content (MC) as a function of temperature, humidity, previous MC, time, precipitation information. model describes MC evolution data more accurately than six mathematical empirical equations typically in literature. correlation coefficient greater 98.8%.
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