Development of Granary Temperature and Humidity Prediction Model Based on RBF Neural Network

DOI

10.2991/icaset-17.2017.31How to use a DOI?

Keywords

RBF neural network, Granary temperature and humidity, Prediction model

Abstract

The traditional prediction methods are generally based on the assumption of linear model. At present, BP neural network and RBF neural network are usually adopted by people in prediction. Since BP neural network has the problem of local optimum and slow training speed, etc., in this paper the method of RBF neural network is adopted in modeling the granary temperature and humidity system, so as to represent the prediction model of granary temperature and humidity system and acquire a recursive prediction model. The experiments results showed that this model can represent the corresponding relationship between the input data vector and the output vector of granary.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Weilin Qiu
AU  - Siqing Yang
PY  - 2017/05
DA  - 2017/05
TI  - Development of Granary Temperature and Humidity Prediction Model Based on RBF Neural Network
BT  - Proceedings of the 2017 7th International Conference on Applied Science, Engineering and Technology (ICASET 2017)
PB  - Atlantis Press
SP  - 163
EP  - 166
SN  - 2352-5401
UR  - https://doi.org/10.2991/icaset-17.2017.31
DO  - 10.2991/icaset-17.2017.31
ID  - Qiu2017/05
ER  -