A VMD and LSTM based hybrid model of load forecasting for power grid security
Lv, L., Wu, Z., Zhang, J., Tan, Z., Zhang, L., & Tian, Z. (2022)
A VMD and LSTM based hybrid model of load forecasting for power grid security. IEEE Transactions on Industrial Informatics, 18(9), 6474-6482. https://doi.org/10.1109/tii.2021.3130237
As the basis for the static security of the power grid, power load forecasting directly affects the safety of grid operation, the rationality of grid planning, and the economy...
Wireless Sensor Networks (WSN) in Oil and Gas Industry: Applications, Requirements and Existing Solutions
Wadhaj, I., Ghaleb, B., & Thomson, C. (2021)
Wireless Sensor Networks (WSN) in Oil and Gas Industry: Applications, Requirements and Existing Solutions. In Proceedings of International Conference on Emerging Technologies and Intelligent Systems ICETIS 2021: Volume 2 (547-563). https://doi.org/10.1007/978-3-030-85990-9_44
Effective measurement and monitoring of certain parameters (temperature, pressure, flow etc.) is crucial for the safety and optimization of processes in the Oil and Gas Indust...
A Novel Prediction-Based Temporal Graph Routing Algorithm for Software-Defined Vehicular Networks
Zhao, L., Li, Z., Al-Dubai, A., Min, G., Li, J., Hawbani, A., & Zomaya, A. (2022)
A Novel Prediction-Based Temporal Graph Routing Algorithm for Software-Defined Vehicular Networks. IEEE Transactions on Intelligent Transportation Systems, 23(8), 13275-13290. https://doi.org/10.1109/TITS.2021.3123276
Temporal information is critical for routing computation in the vehicular network. It plays a vital role in the vehicular network. Till now, most existing routing schemes in v...
Performance of Cognitive Radio Sensor Networks Using Hybrid Automatic Repeat ReQuest: Stop-and-Wait
Khan, F., ur Rehman, A., Usman, M., Tan, Z., & Puthal, D. (2018)
Performance of Cognitive Radio Sensor Networks Using Hybrid Automatic Repeat ReQuest: Stop-and-Wait. Mobile Networks and Applications, https://doi.org/10.1007/s11036-018-1020-4
The enormous developments in the field of wireless communication technologies have made the unlicensed spectrum bands crowded, resulting uncontrolled interference to the tradi...
Estimating 3D trajectories from 2D projections via disjunctive factored four-way conditional restricted Boltzmann machines
Mocanu, D. C., Bou Ammar, H., Puig, L., Eaton, E., & Liotta, A. (2017)
Estimating 3D trajectories from 2D projections via disjunctive factored four-way conditional restricted Boltzmann machines. Pattern Recognition, 69, 325-335. https://doi.org/10.1016/j.patcog.2017.04.017
Estimation, recognition, and near-future prediction of 3D trajectories based on their two dimensional projections available from one camera source is an exceptionally difficul...
A Novel Time-Slotted LoRa MAC Protocol for Scalable IoT Networks
Alahmadi, H., Bouabdallah, F., & Al-Dubai, A. (2022)
A Novel Time-Slotted LoRa MAC Protocol for Scalable IoT Networks. Future Generation Computer Systems, 134, 287-302. https://doi.org/10.1016/j.future.2022.04.003
Long Range (LoRa) networks provide long range, cost-effective and energy-efficient communications by utilising the free unlicensed ISM band, which makes them appealing for Int...
Self-Learning Power Control in Wireless Sensor Networks
Chincoli, M., & Liotta, A. (2018)
Self-Learning Power Control in Wireless Sensor Networks. Sensors, 18(2), 1-29. https://doi.org/10.3390/s18020375
Current trends in interconnecting myriad smart objects to monetize on Internet of Things applications have led to high-density communications in wireless sensor networks. This...
A Novel Cost Optimization Strategy for SDN-Enabled UAV-Assisted Vehicular Computation Offloading
Zhao, L., Yang, K., Tan, Z., Li, X., Sharma, S., & Liu, Z. (2021)
A Novel Cost Optimization Strategy for SDN-Enabled UAV-Assisted Vehicular Computation Offloading. IEEE Transactions on Intelligent Transportation Systems, 22(6), 3664-3674. https://doi.org/10.1109/TITS.2020.3024186
Vehicular computation offloading is a well-received strategy to execute delay-sensitive and/or compute-intensive tasks of legacy vehicles. The response time of vehicular compu...
On-Line Building Energy Optimization Using Deep Reinforcement Learning
Mocanu, E., Mocanu, D. C., Nguyen, P. H., Liotta, A., Webber, M. E., Gibescu, M., & Slootweg, J. G. (2019)
On-Line Building Energy Optimization Using Deep Reinforcement Learning. IEEE Transactions on Smart Grid, 10(4), 3698-3708. https://doi.org/10.1109/tsg.2018.2834219
Unprecedented high volumes of data are becoming available with the growth of the advanced metering infrastructure. These are expected to benefit planning and operation of the ...
Spatial anomaly detection in sensor networks using neighborhood information
Bosman, H. H., Iacca, G., Tejada, A., Wörtche, H. J., & Liotta, A. (2017)
Spatial anomaly detection in sensor networks using neighborhood information. Information Fusion, 33, 41-56. https://doi.org/10.1016/j.inffus.2016.04.007
The field of wireless sensor networks (WSNs), embedded systems with sensing and networking capability, has now matured after a decade-long research effort and technological ad...