| Tool wear classification using time series imaging and deep learning G Martínez-Arellano, G Terrazas, S Ratchev The International Journal of Advanced Manufacturing Technology 104, 3647-3662, 2019 | 180 | 2019 |
| In-process tool wear prediction system based on machine learning techniques and force analysis A Gouarir, G Martínez-Arellano, G Terrazas, P Benardos, S Ratchev Procedia CIRP 77, 501-504, 2018 | 167 | 2018 |
| Online tool wear classification during dry machining using real time cutting force measurements and a CNN approach G Terrazas, G Martínez-Arellano, P Benardos, S Ratchev Journal of Manufacturing and Materials Processing 2 (4), 72, 2018 | 45 | 2018 |
| Creating AI characters for fighting games using genetic programming G Martinez-Arellano, R Cant, D Woods IEEE transactions on computational intelligence and Ai in games 9 (4), 423-434, 2016 | 34 | 2016 |
| Towards an active learning approach to tool condition monitoring with bayesian deep learning G Martinez Arellano, S Ratchev | 20 | 2019 |
| Towards modular and plug-and-produce manufacturing apps A Torayev, G Martínez-Arellano, JC Chaplin, D Sanderson, S Ratchev Procedia CIRP 107, 1257-1262, 2022 | 12 | 2022 |
| Prediction of jet engine parameters for control design using genetic programming GM Arellano, R Cant, L Nolle 2014 UKSim-AMSS 16th International Conference on Computer Modelling and …, 2014 | 12 | 2014 |
| Characterisation of large changes in wind power for the day-ahead market using a fuzzy logic approach G Martínez-Arellano, L Nolle, R Cant, A Lotfi, C Windmill KI-Künstliche Intelligenz 28, 239-253, 2014 | 10 | 2014 |
| A data analytics model for improving process control in flexible manufacturing cells G Martínez-Arellano, TB Nguyen, C Hinton, S Ratchev Decision Analytics Journal 3, 100075, 2022 | 8 | 2022 |
| Short-term wind power forecasting with WRF-ARW model and genetic programming G Martinez-Arellano, L Nolle Proc. Int. Conf. Soft Computing, 2013 | 8 | 2013 |
| XOR binary gravitational search algorithm with repository: industry 4.0 applications M Ahmadieh Khanesar, R Bansal, G Martínez-Arellano, DT Branson Applied Sciences 10 (18), 6451, 2020 | 7 | 2020 |
| Improving WRF-ARW wind speed predictions using genetic programming G Martinez-Arellano, L Nolle, J Bland International Conference on Innovative Techniques and Applications of …, 2012 | 6 | 2012 |
| Trustworthy, responsible, ethical AI in manufacturing and supply chains: synthesis and emerging research questions A Brintrup, G Baryannis, A Tiwari, S Ratchev, G Martinez-Arellano, ... arXiv preprint arXiv:2305.11581, 2023 | 5 | 2023 |
| Visualisation on a Shoestring: a low-cost approach for building visualisation components of industrial digital solutions G Martínez-Arellano, MJ McNally, JC Chaplin, Z Ling, D McFarlane, ... International Workshop on Service Orientation in Holonic and Multi-Agent …, 2021 | 5 | 2021 |
| Digital twins and intelligent decision making JC Chaplin, G Martinez-Arellano, A Mazzoleni DIGITAL MANUFACTURING FOR SMEs-An Introduction. Digital Manufacturing …, 2020 | 5 | 2020 |
| Genetic programming for wind power forecasting and ramp detection G Martínez-Arellano, L Nolle International Conference on Innovative Techniques and Applications of …, 2013 | 5 | 2013 |
| Semantic models and knowledge graphs as manufacturing system reconfiguration enablers F Mo, JC Chaplin, D Sanderson, G Martínez-Arellano, S Ratchev Robotics and Computer-Integrated Manufacturing 86, 102625, 2024 | 4 | 2024 |
| Capacity modelling and measurement for smart elastic manufacturing systems B Elshafei, F Mo, JC Chaplin, GM Arellano, S Ratchev SAE Technical Paper, 2023 | 4 | 2023 |
| Comparison of simple encoding schemes in GA’s for the motif finding problem: Preliminary results G Martínez-Arellano, CA Brizuela Brazilian Symposium on Bioinformatics, 22-33, 2007 | 4 | 2007 |
| Classification of cancer cells at the sub-cellular level by phonon microscopy using deep learning F Pérez-Cota, G Martínez-Arellano, S La Cavera III, W Hardiman, ... Scientific Reports 13 (1), 16228, 2023 | 3 | 2023 |
