Application of Data Fusion on System of Measurement and Control for Grain Storage

Author

Zhu, Yuhua ; Zhen, Tong ; Ma, Zhi

Author_Institution

Coll. of Inf. Sci. & Eng., Henan Univ. of Technol., Zhengzhou, China

fYear

2009

fDate

11-12 July 2009

Firstpage

116

Lastpage

119

Abstract

Data fusion was used to predict the safe value of grain environment in different operational conditions. The temperature, humidity, moisture, pest and etc., were used as inputs to the data fusion center and network. Feed-forward artificial neural networks with 4-10-5 arrangements were capable to estimate the safe value of grain environment as the outputs. This method, characterized by sufficiently utilizing the effective detected data, optimizing homogeneous data, and considering the complementation of the different data source makes possible an improvement in the reliability and entirety of detection system.

Keywords

feedforward neural nets; sensor fusion; data fusion; detection system; feedforward artificial neural networks; grain storage; safe value; Artificial intelligence; Artificial neural networks; Automatic control; Control nonlinearities; Control systems; Data engineering; Educational institutions; Information science; Nonlinear control systems; Target recognition; BP neural network; Data fusion; Sensor fusion;

fLanguage

English

Publisher

ieee

Conference_Titel

Control, Automation and Systems Engineering, 2009. CASE 2009. IITA International Conference on

Conference_Location

Zhangjiajie

Print_ISBN

978-0-7695-3728-3

Type

conf

DOI

10.1109/CASE.2009.36

Filename

5194404