| Is your dataset big enough? Sample size requirements when using artificial neural networks for discrete choice analysis A Alwosheel, S van Cranenburgh, CG Chorus Journal of choice modelling 28, 167-182, 2018 | 355 | 2018 |
| An artificial neural network based approach to investigate travellers’ decision rules S van Cranenburgh, A Alwosheel Transportation Research Part C: Emerging Technologies 98, 152-166, 2019 | 77 | 2019 |
| Heart rate variability estimation in photoplethysmography signals using Bayesian learning approach A Alqaraawi, A Alwosheel, A Alasaad Healthcare technology letters 3 (2), 136-142, 2016 | 54 | 2016 |
| Why did you predict that? Towards explainable artificial neural networks for travel demand analysis A Alwosheel, S van Cranenburgh, CG Chorus Transportation Research Part C: Emerging Technologies 128, 103143, 2021 | 26 | 2021 |
| ‘Computer says no’is not enough: Using prototypical examples to diagnose artificial neural networks for discrete choice analysis A Alwosheel, S Van Cranenburgh, CG Chorus Journal of choice modelling 33, 100186, 2019 | 16 | 2019 |
| Trustworthy and Explainable Artificial Neural Networks for Choice Behaviour Analysis ASA Alwosheel | 7 | 2020 |
| Artificial neural networks as a means to accommodate decision rules in choice models A Alwosheel, C Chorus, S van Cranenburgh International Choice Modelling Conference 2017, 2017 | 5 | 2017 |
| Towards efficient heart rate variability estimation in artifact-induced Photoplethysmography signals A Alqaraawi, A Alwosheel, A Alasaad 2016 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE …, 2016 | 5 | 2016 |
| Using artificial neural networks to investigate decision-rule heterogeneity S van Cranenburgh, A Alwosheel 6th Symposium of the European Association for Research in Transportation …, 2017 | 4 | 2017 |
| Using prototypical examples to diagnose artificial neural networks for discrete choice analysis A Alwosheel, S Van Cranenburgh, C Chorus International Choice Modelling Conference 2019, 2019 | | 2019 |
| Travel behavior analysis using Artificial Neural Networks: Striking the balance between model complexity and data requirements A Alwosheel, S van Cranenburgh, C Chorus IATBR 2018: 15th International Conference on Travel Behaviour Research, 2018 | | 2018 |
| Explaining predictions of artificial neural networks for travel behaviour analysis using layer-wise relevance propagation A Alwosheel, S van Cranenburgh, CG Chorus | | |
| Trustworthy and Explainable Artificial Neural Networks for Choice Behaviour Analysis A Saleh, A Alwosheel | | |
| A Two-Step Framework for Unsupervised Speaker Segmentation Using BIC and Artificial Neural Network A Alwosheel, A Alqaraawi | | |
| Unsupervised Reciter Recognition Using Gaussian Mixture Models A Alwosheel, A Alqaraawi | | |
Sander van CranenburghAssociate professor, Delft University of TechnologyGeverifieerd e-mailadres voor tudelft.nl
