Paal Engelstad

Vitenskapelige publikasjoner

Rauniyar, Ashish; Østerbø, Olav; Håkegård, Jan Erik; Engelstad, Paal E. (2023). Exploiting Cooperative Downlink NOMA in D2D Communications. 17 s. Sensors. Vol. 23.
https://doi.org/10.3390/s23083958

Rauniyar, Ashish; Østerbø, Olav Norvald; Håkegård, Jan Erik; Engelstad, Paal E. (2022). Secrecy Performance Analysis of Cooperative Nonorthogonal Multiple Access in IoT Networks. 15 s. IEEE Sensors Journal. Vol. 22.
https://doi.org/10.1109/JSEN.2022.3199540

Abolghasemi, Roza; Engelstad, Paal E.; Herrera-Viedma, Enrique; Yazidi, Anis (2022). A personality-aware group recommendation system based on pairwise preferences. Information Sciences. Vol. 595.
https://doi.org/10.1016/j.ins.2022.02.033

Holen, Martin; Ruud, Else-Line Malene; Warakagoda, Narada Dilp; Granmo, Ole-Christoffer; Engelstad, Paal E.; Knausgård, Kristian Muri (2022). Towards Using Reinforcement Learning for Autonomous Docking of Unmanned Surface Vehicles. Iliadis, Lazaros; Jayne, Chrisina; Tefas, Anastasios; Pimenidis, Elias (Red.). Engineering Applications of Neural Networks. EANN 2022. Communications in Computer and Information Science. s. 461-474. Springer Nature.
https://doi.org/10.1007/978-3-031-08223-8_38

Bentsen, Lars Ødegaard; Warakagoda, Narada Dilp; Stenbro, Roy; Engelstad, Paal (2022). Spatio-temporal wind speed forecasting using graph networks and novel Transformer architectures. 13 s. Applied Energy. Vol. 333.
https://doi.org/10.1016/j.apenergy.2022.120565

Bentsen, Lars Ødegaard; Warakagoda, Narada Dilp; Stenbro, Roy; Engelstad, Paal (2022). Probabilistic Wind Park Power Prediction using Bayesian Deep Learning and Generative Adversarial Networks. 10 s. Journal of Physics: Conference Series (JPCS). Vol. 2362.
https://doi.org/10.1088/1742-6596/2362/1/012005

Bentsen, Lars Ødegaard; Warakagoda, Narada Dilp; Stenbro, Roy; Engelstad, Paal (2022). Wind Park Power Prediction: Attention-Based Graph Networks and Deep Learning to Capture Wake Losses. Journal of Physics: Conference Series (JPCS). Vol. 2265.
https://doi.org/10.1088/1742-6596/2265/2/022035

Meng, Li; Goodwin, Morten; Yazidi, Anis; Engelstad, Paal (2022). Improving the Diversity of Bootstrapped DQN by Replacing Priors With Noise. 10 s. IEEE Transactions on Games (TG).
https://doi.org/10.1109/TG.2022.3185330

Meng, Li; Yazidi, Anis; Goodwin, Morten; Engelstad, Paal (2022). Expert Q-learning: Deep Reinforcement Learning with Coarse State Values from Offline Expert Examples. 9 s. Proceedings of the Northern Lights Deep Learning Workshop.
https://doi.org/10.7557/18.6237

Abolghasemi, Roza; Khadka, Rabindra; Lind, Pedro; Engelstad, Paal E.; Viedma, Enrique Herrera; Yazidi, Anis (2022). Predicting missing pairwise preferences from similarity features in group decision making. Knowledge-Based Systems. Vol. 256.
https://doi.org/10.1016/j.knosys.2022.109860

Forskningsrapporter

Østerbø, Olav Norvald; Engelstad, Paal E. (2008). WLAN QoS Analysis - A New Modelling Approach for 802.11e, Telenor R&I Scientific Report, R28/08. 20 s. Telenor R&I.

Jønvik, Tore; Engelstad, Paal; Do, Thanh van (2005). Towards the realisation of the Virtual Device Consept. 222 s. Unipub forlag.

Formidling

Aryan, Ramtin; Brattensborg, Frode; Yazidi, Anis; Engelstad, Paal E. (2019). Checking the OpenFlow Rule Installation and Operational Verification. The 44th IEEE Conference on Local Computer Networks (LCN). IEEE.

HaileselassieHagos, Desta; Engelstad, Paal E.; Yazidi, Anis (2019). Classification of Delay-based TCP Algorithms From Passive Traffic Measurements. ©2019 IEEE. IEEE.

Aryan, Ramtin; Yazidi, Anis; Engelstad, Paal E. (2018). An Incremental Approach for Swift OpenFlow Anomaly Detection. 2018 IEEE 43rd Conference on Local Computer Networks (LCN). IEEE.

Aryan, Ramtin; Yazidi, Anis; Engelstad, Paal E.; Kure, Øivind (2017). A General Formalism for Defining and Detecting OpenFlow Rule Anomalies. 2017 IEEE 42nd Conference on Local Computer Networks. IEEE 42nd Conference on Local Computer Networks.

Van Thuan, Do; Engelstad, Paal E.; Feng, Boning; Do, van Thanh (2017). Detection of DNS tunneling in mobile networks using machine learning. International Conference on Information Science and Applications 2017 ICISA 2017.

Do, van Thanh; Engelstad, Paal E.; Feng, Boning; Do, Van Thuan (2017). A near real time SMS Grey Traffic detection. 6th International Conference on Software and Computer Applications.

Do, Van Thuan; Engelstad, Paal E.; Boning, Feng; Do, van Thanh (2016). Strengthening mobile network security using machine learning. 13th International Conference on Mobile Web and Intelligent Information Systems. Natalia Kryvinska, University of Vienna, Austria .

Yazidi, Anis; Bai, Aleksander; Hammer, Hugo Lewi; Engelstad, Paal E. (2015). A Simple and Efficient Algorithm for Lexicon Generation Inspired by Structural Balance Theory. 28th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems.

Yazidi, Anis; Hammer, Hugo Lewi; Bai, Aleksander; Engelstad, Paal E. (2015). On Enhancing the Label Propagation Algorithm for Sentiment Analysis Using Active Learning with an Artificial Oracle. Artificial Intelligence and Soft Computing: 14th International Conference, ICAISC 2015.

Engelstad, Paal E.; Hammer, Hugo Lewi; Yazidi, Anis; Bai, Aleksander (2015). Advanced Classification Lists (Dirty Word Lists) for Automatic Security Classification. International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC).