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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: 2023 | 2022 | 2021
Number of items: 7.

2023

Powell, Cheyenne and Riccardi, Annalisa (2023) Question answering over knowledge graphs for explainable satellite scheduling. In: International Astronautical Congress, 2023-10-02 - 2023-10-06, Heydar Aliyev Center.

Powell, Cheyenne and Berquand, Audrey and Riccardi, Annalisa (2023) Natural language processing for explainable satellite scheduling. In: SPACEOPS 2023, 2023-03-06 - 2023-03-10.

Powell, Cheyenne and Riccardi, Annalisa; Huang, Joshua Zhexue and Pan, Yi and Hammer, Barbara and Khan, Muhammad Khurram and Xie, Xing and Cui, Laizhong and He, Yulin, eds. (2023) Abstract argumentation for explainable satellite scheduling. In: 2022 IEEE 9th International Conference on Data Science and Advanced Analytics (DSAA). IEEE, CHN, pp. 1-10. ISBN 9781665473309

2022

Hall, Iain and Powell, Cheyenne and Riccardi, Annalisa (2022) Constraint programming for scheduling the operations of STRATHcube : a nanosatellite for detecting space debris. In: 73rd International Astronautical Congress (IAC), 2022-09-18 - 2022-10-22, Paris Convention Centre.

Powell, Cheyenne and Riccardi, Annalisa (2022) On-board re-planning of an earth observation satellite for maximisation of observation campaign goals. In: 73rd International Astronautical Congress (IAC), 2022-09-18 - 2022-10-22, Paris Convention Centre.

2021

Powell, Cheyenne and Riccardi, Annalisa (2021) Towards explainability of on-board satellite scheduling for end user interactions. In: 72nd International Astronautical Congress, 2021-10-25 - 2021-10-29, Dubai World Trade Centre.

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 . Springer, ESP, pp. 187-202. ISBN 9783030729141

This list was generated on Mon May 27 08:30:04 2024 BST.