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12 January 2018 Research on wind field algorithm of wind lidar based on BP neural network and grey prediction
Yong Chen, Chun-Li Chen, Xiong Luo, Yan Zhang, Ze-hou Yang, Jie Zhou, Xiao-ding Shi, Lei Wang
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Proceedings Volume 10619, 2017 International Conference on Optical Instruments and Technology: Advanced Laser Technology and Applications; 106190O (2018) https://doi.org/10.1117/12.2295346
Event: International Conference on Optical Instruments and Technology 2017, 2017, Beijing, China
Abstract
This paper uses the BP neural network and grey algorithm to forecast and study radar wind field. In order to reduce the residual error in the wind field prediction which uses BP neural network and grey algorithm, calculating the minimum value of residual error function, adopting the residuals of the gray algorithm trained by BP neural network, using the trained network model to forecast the residual sequence, using the predicted residual error sequence to modify the forecast sequence of the grey algorithm. The test data show that using the grey algorithm modified by BP neural network can effectively reduce the residual value and improve the prediction precision.
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Yong Chen, Chun-Li Chen, Xiong Luo, Yan Zhang, Ze-hou Yang, Jie Zhou, Xiao-ding Shi, and Lei Wang "Research on wind field algorithm of wind lidar based on BP neural network and grey prediction", Proc. SPIE 10619, 2017 International Conference on Optical Instruments and Technology: Advanced Laser Technology and Applications, 106190O (12 January 2018); https://doi.org/10.1117/12.2295346
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KEYWORDS
Neural networks
Evolutionary algorithms
LIDAR
Data modeling
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