An Improved Stacked Denoise Autoencoder with Elu Activation Function for Traffic Data Imputation
2019 ◽
Vol 8
(11)
◽
pp. 3951-3954
Keyword(s):
Traffic data plays a major role in transport related applications. The problem of missing data has greatly impact the performance of Intelligent transportation systems(ITS). In this work impute the missing traffic data with spatio-temporal exploitation for high precision result under various missing rates. Deep learning based stacked denoise autoencoder is proposed with efficient Elu activation function to remove noise and impute the missing value.This imputed value will be used in analyses and prediction of vehicle traffic. Results are discussed that the proposed method outperforms well in state of the art approaches.
2021 ◽
Vol 9
(6)
◽
pp. 30-38
2020 ◽
pp. 1-10
2021 ◽
pp. 1-10
2015 ◽
Vol 75
(19)
◽
pp. 11683-11698
◽
2020 ◽
Vol 69
(11)
◽
pp. 12510-12520
2020 ◽
pp. 1-9
2011 ◽
Vol 12
(1)
◽
pp. 194-200
◽
2019 ◽
Vol 8
(11)
◽
pp. 845-849