temperature and relative humidity estimation and prediction in the tobacco drying process using artificial neural networks温度和相对湿度的估计和预测烟草干燥过程中使用人工神经网络.pdf

Sensors 2012, 12, 14004-14021; doi:10.3390/s121014004 OPEN ACCESS sensors ISSN 1424-8220 /journal/sensors Article Temperature and Relative Humidity Estimation and Prediction in the Tobacco Drying Process Using Artificial Neural Networks Víctor Martínez-Martínez 1,*, Carlos Baladrón 1, Jaime Gomez-Gil 1, Gonzalo Ruiz-Ruiz 2, Luis M. Navas-Gracia 2, Javier M. Aguiar 1 and Belén Carro 1 1 Department of Signal Theory, Communications and Telematics Engineering, University of Valladolid, 47011 Valladolid, Spain; E-Mails: cbalzor@ribera.tel.uva.es (C.B.); jgomez@tel.uva.es (J.G. -G.); javagu@tel.uva.es (J.M.A.); belcar@tel.uva.es (B.C.) 2 Department of Agricultural and Forestry Engineering, University of Valladolid, 34004 Palencia, Spain; E-Mails: gruiz@iaf.uva.es (G.R.-R.); lmnavas@iaf.uva.es (L.M.N.-G.) * Author to whom correspondence should be addressed; E-Mail: vmarmar@ribera.tel.uva.es; Tel.: +34-636-797-528; Fax: +34-983-423-667. Received: 2 August 2012; in revised form: 28 September 2012 / Accepted: 6 October 2012 / Published: 17 October 2012 Abstract: This paper presents a system based on an Artificial Neural Network (ANN) for estimating and predicting environmental variables related to tobacco drying processes. This system has been validated with temperature and relative humidity data obtained from a real tobacco dryer with a Wireless Sensor Network (WSN). A fitting ANN was used to estimate temperature and relative humidity in different locations inside t