A two-stage approach for the remaining useful life prediction of bearings using deep neural networks M Xia, T Li, T Shu, J Wan, CW De Silva, Z Wang IEEE Transactions on Industrial Informatics 15 (6), 3703-3711, 2018 | 235 | 2018 |
An energy-efficient dual prediction scheme using LMS filter and LSTM in wireless sensor networks for environment monitoring T Shu, J Chen, VK Bhargava, CW de Silva IEEE Internet of Things Journal 6 (4), 6736-6747, 2019 | 65 | 2019 |
An energy efficient adaptive sampling algorithm in a sensor network for automated water quality monitoring T Shu, M Xia, J Chen, C De Silva Sensors 17 (11), 2551, 2017 | 45 | 2017 |
Deep reinforced learning tree for spatiotemporal monitoring with mobile robotic wireless sensor networks J Chen, T Shu, T Li, CW de Silva IEEE Transactions on Systems, Man, and Cybernetics: Systems 50 (11), 4197-4211, 2019 | 31 | 2019 |
Using geometric centroid of Voronoi diagram for coverage and lifetime optimization in mobile wireless sensor networks T Shu, KB Dsouza, V Bhargava, C de Silva 2019 IEEE Canadian Conference of Electrical and Computer Engineering (CCECE …, 2019 | 19 | 2019 |
Rapidly-exploring tree with linear reduction: A near-optimal approach for spatiotemporal sensor deployment in aquatic fields using minimal sensor nodes J Chen, T Li, T Shu, CW De Silva IEEE Sensors Journal 18 (24), 10225-10239, 2018 | 11 | 2018 |
WSN optimization for sampling-based signal estimation using semi-binarized variational autoencoder J Chen, J Wang, T Shu, CW de Silva Information Sciences 587, 188-205, 2022 | 4 | 2022 |
Power management in a sensor network for automated water quality monitoring T Shu University of British Columbia, 2016 | 3 | 2016 |
Energy efficient schemes in a mobile sensor network with application in automated monitoring of water quality T Shu University of British Columbia, 2020 | | 2020 |