Modify Manual Observation System Data to Automatic Observing System Data on Wind Speed Using Bp Neural Network

Author

Zhang, Wen-Yu ; Liu, Xin ; Liu, Xuan ; Huang, Shan ; Lin, Hai-Feng ; Kong, Ling-Bin

Author_Institution

Key Lab. of Arid Climatic Change & Reducing Disaster of Gansu Province, Lanzhou Univ., Lanzhou, China

fYear

2010

fDate

29-31 Oct. 2010

Firstpage

1

Lastpage

4

Abstract

This paper uses back propagation (BP) neural network to modify manual observing system data to automatic observing system data in wind speed data. First, we prepare six factors which are wind speed data six hours ahead to one hour ahead as input data. The tests indict when these factors selected, the modify results are better than others. The training data used for the neural network is the data from 1 Jan 2005 to 31 Dec 2007. The data from 1 Jan 2004 to 31 Dec 2004 are employed to test the model. The results show that the proposed method can produce satisfactory results in modifying manual observing system data to automatic observing system data. After modifying the manual data using BP neural network, the modified time series achieves -0.05m/s in Mean Bias Error compared to automatic observing system data. For wind speed, it could be a promising candidate for modifying manual observing system data to automatic observing system data.

Keywords

backpropagation; geophysics computing; meteorology; neural nets; time series; wind; BP neural network; automatic observing system data; back propagation neural network; manual observation system data; mean bias error; modified time series; wind speed; Artificial neural networks; Data models; Manuals; Neurons; Training; Wind speed;

fLanguage

English

Publisher

ieee

Conference_Titel

Multimedia Technology (ICMT), 2010 International Conference on

Conference_Location

Ningbo

Print_ISBN

978-1-4244-7871-2

Type

conf

DOI

10.1109/ICMULT.2010.5631119

Filename

5631119