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Open Access research that better understands changing marine ecologies...

Strathprints makes available scholarly Open Access content by researchers in the Department of Mathematics & Statistics.

Mathematics & Statistics hosts the Marine Population Modelling group which is engaged in research into topics surrounding marine resource modelling and ecology. Recent work has included important developments in the population modelling of marine species.

Explore the Open Access research of Mathematics & Statistics. Or explore all of Strathclyde's Open Access research...

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Jump to: 2024 | 2023 | 2022 | 2021 | 2020
Number of items: 11.

2024

Wilson, Callum J. and Vasile, Massimiliano and Feng, Jinglang and McNally, Keiran and Antón, Alfredo and Letizia, Francesca; (2024) Modelling future launch traffic and its effect on the LEO operational environment. In: AIAA SciTech 2024 Forum. American Institute of Aeronautics and Astronautics, USA. ISBN 9781624107115

2023

Wilson, Callum and Vasile, Massimiliano and Feng, Jinglang and McNally, Keiran and Anton, Alfredo and Letizia, Francesca (2023) Quantifying the induced and encountered risk of space missions. In: 74th International Astronautical Congress, 2023-10-02 - 2023-10-06.

Wang, Yirui and Wilson, Callum and Vasile, Massimiliano (2023) Multi-layer temporal network model of the space environment. In: 2023 AAS/AIAA Astrodynamics Specialist Conference, 2023-08-13 - 2023-08-17, Big Sky Resort.

2022

Wilson, Callum and Riccardi, Annalisa (2022) Enabling intelligent onboard guidance, navigation, and control using reinforcement learning on near-term flight hardware. Acta Astronautica, 199. pp. 374-385. ISSN 0094-5765

2021

Wilson, Callum and Riccardi, Annalisa (2021) Enabling intelligent onboard guidance, navigation, and control using near-term flight hardware. In: 72nd International Astronautical Congress, 2021-10-25 - 2021-10-29, Dubai World Trade Centre.

Wilson, Callum and Riccardi, Annalisa (2021) Improving the efficiency of reinforcement learning for a spacecraft powered descent with Q-learning. Optimization and Engineering, 24 (1). pp. 223-255. ISSN 1389-4420

Wilson, Callum and Riccardi, Annalisa (2021) Leveraging optimal control demonstrations in reinforcement learning for powered descent. In: 8th International Conference on Astrodynamics Tools and Techniques, 2021-06-22 - 2021-06-25, Virtual.

Marchetti, Francesco and Wilson, Callum and Powell, Cheyenne and Minisci, Edmondo and Riccardi, Annalisa; Romero, Juan and Martins, Tiago and Rodríguez-Fernández, Nereida, eds. (2021) Convolutional Generative Adversarial Network, via Transfer Learning, for traditional Scottish music generation. In: Artificial Intelligence in Music, Sound, Art and Design. Lecture Notes in Computer Science, 12693 . Springer, ESP. ISBN 978-3-030-72914-1

2020

Wilson, Callum and Riccardi, Annalisa and Minisci, Edmondo; (2020) A novel update mechanism for Q-Networks based on extreme learning machines. In: 2020 International Joint Conference on Neural Networks (IJCNN). IEEE, GBR. ISBN 9781728169262

Wilson, Callum and Marchetti, Francesco and Di Carlo, Marilena and Riccardi, Annalisa and Minisci, Edmondo (2020) Classifying intelligence in machines : a taxonomy of intelligent control. Robotics, 9 (3). 64. ISSN 2218-6581

Wilson, Callum and Marchetti, Francesco and Di Carlo, Marilena and Riccardi, Annalisa and Minisci, Edmondo (2020) Intelligent control : a taxonomy. In: 8th International Conference on Systems and Control, 2019-10-23 - 2019-10-25, Faculty of sciences Semlalia, Cadi Ayyad University.

This list was generated on Sat Apr 20 05:46:34 2024 BST.