EXTENSION OF THE NEURAL NETWORKS OPERATING RANGE BY THE APPLICATION OF DIMENSIONLESS NUMBERS IN PREDICTION OF HEAT TRANSFER COEFFICIENTS
作者:
Ireneusz ZBICIŃSKI,
Krzysztof CIESIELSKI,
期刊:
Drying Technology
(Taylor Available online 2000)
卷期:
Volume 18,
issue 3
页码: 649-660
ISSN:0737-3937
年代: 2000
DOI:10.1080/07373930008917730
出版商: Taylor & Francis Group
关键词: fluidised bed drying;;hybrid neural modelling
数据来源: Taylor
摘要:
The paper presents a study aimed at extending the neural network mapping ability. In traditional modelling, operational process parameters (gas/material temperature, air velocity, etc.) are the inputs and outputs to and from the network. In this approach dimensionless numbers (Re, Ar, H/d) were used as inputs to predict the heat transfer coefficient in a fluidised bed drying process. To produce the data set necessary to train the networks, drying trials of different materials in a fluidised bed were carried out.
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