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Zhao, Zhongliang; Emami, Negar; Santos, Hugo; Pacheco, Lucas; Karimzadeh, Mostafa; Braun, Torsten; Braud, Arnaud; Radier, Benoit; Tamagnan, Philippe (2022). Reinforced-LSTM Trajectory Prediction-driven Dynamic Service Migration: A Case Study. Transactions on Network Science and Engineering, 9(4), pp. 2786-2802. IEEE 10.1109/TNSE.2022.3169786
Karimzadeh, Mostafa; Esposito, Alessandro; Zhao, Zhongliang; Braun, Torsten; Sargento, Susana (28 June 2021). RL-CNN: Reinforcement Learning-designed Convolutional Neural Network for Urban Traffic Flow Estimation. In: 17th International Wireless Communications & Mobile Computing Conference - IWCMC 2021 (pp. 29-34). IEEE 10.1109/IWCMC51323.2021.9498948
Karimzadeh, Mostafa; Schwegler, Samuel Martin; Zhao, Zhongliang; Braun, Torsten; Sargento, Susana (28 June 2021). MTL-LSTM: Multi-Task Learning-based LSTM for Urban Traffic Flow Forecasting. In: 17th International Wireless Communications & Mobile Computing Conference - IWCMC 2021 (pp. 564-569). IEEE 10.1109/IWCMC51323.2021.9498905
Karimzadeh, Mostafa; Aebi, Ryan; M. de Souza, Allan; Zhao, Zhongliang; Braun, Torsten; Sargento, Susana; Villas, Leandro (5 May 2021). Reinforcement Learning-designed LSTM for Trajectory and Traffic Flow Prediction. In: IEEE Wireless Communications and Networking Conference (pp. 1-6). IEEE 10.1109/WCNC49053.2021.9417511
Karimzadeh, Mostafa (2020). Prediction Models to Enhance Location Based Services in Urban Areas. (Dissertation, Institute for computer science, Faculty of Science)
Zhao, Zhongliang; Karimzadeh, Mostafa; Pacheco, Lucas; Santos, Hugo; Rosário, Denis; Braun, Torsten; Cerqueira, Eduardo (29 October 2020). Mobility Management with Transferable Reinforcement Learning Trajectory Prediction. IEEE Transactions on Network and Service Management, 17(4), pp. 2102-2116. IEEE 10.1109/TNSM.2020.3034482
Karimzadeh Motallebiazar, Mostafa; Mariano de Souza, Allan; Zhao, Zhongliang; Braun, Torsten; Villas, Leandro; Sargento, Susana; Loureiro, Antonio A. F. (2020). Intelligent Safety Message Dissemination with Vehicle Trajectory Density Predictions in VANETs (Submitted) IEEE Transactions on Vehicular Technology Special Issue on Vehicular Networks in the era of 6G: IEEE
Zhao, Zhongliang; Karimzadeh Motallebiazar, Mostafa; Pacheco, Lucas; Melo dos Santos, Hugo Leonardo; Rosario, Denis; Braun, Torsten; Cerqueira, Eduardo (2020). 5G UDN Proactive Handover with Transferable Reinforcement Learning-based Trajectory Prediction (Submitted). IEEE journal on selected areas in communications IEEE
Schiller, Eryk Jerzy; Röthlisberger, Remo; Braun, Torsten; Karimzadeh Motallebiazar, Mostafa (17 June 2019). Improving Video Delivery with Fourier Analysis of Traffic in Multi-Access Edge Computing. Lecture notes in computer science, 11618, pp. 209-221. Springer 10.1007/978-3-030-30523-9_17
Karimzadeh, Mostafa; Gerber, Florian; Zhao, Zhongliang; Braun, Torsten (18 March 2019). Pedestrians Trajectory Prediction in Urban Environments. In: International Conference on Networked Systems (NetSys). München. 18. - 21.03.2019. 10.1109/NetSys.2019.8854506
Karimzadeh Motallebiazar, Mostafa; Zhao, Zhongliang; Gerber, Florian; Braun, Torsten (4 October 2018). Mobile Users Location Prediction with Complex Behavior Understanding. In: IEEE Conference on Local Computer Networks (IEEE LCN). Chicago, USA. October 1-4, 2018. 10.1109/LCN.2018.8638045
Zhao, Zhongliang; Guardalben, Lucas; Karimzadeh Motallebiazar, Mostafa; Silva, Jose; Braun, Torsten; Sargento, Susana (2018). Mobility Prediction-Assisted Over-The-Top Edge Prefetching for Hierarchical VANETs. IEEE journal on selected areas in communications, 36(8), p. 1. IEEE 10.1109/JSAC.2018.2844681
Karimzadeh Motallebiazar, Mostafa; Zhao, Zhongliang; Gerber, Florian; Braun, Torsten (20 August 2018). Pedestrians Complex Behavior Understanding and Prediction with Hybrid Markov Chain. In: The Eleventh International Workshop on Selected Topics in Wireless and Mobile computing (STWiMob-2018).
Zhao, Zhongliang; Karimzadeh Motallebiazar, Mostafa; Gerber, Florian; Braun, Torsten (2018). Mobile Crowd Location Prediction with Hybrid Features using Ensemble Learning. Future Generation Computer Systems, 110, pp. 556-571. Elsevier 10.1016/j.future.2018.06.025
