| Modeling mandatory lane changing using Bayes classifier and decision trees Y Hou, P Edara, C Sun IEEE Transactions on Intelligent Transportation Systems 15 (2), 647-655, 2013 | 239 | 2013 |
| Traffic flow forecasting for urban work zones Y Hou, P Edara, C Sun IEEE transactions on intelligent transportation systems 16 (4), 1761-1770, 2014 | 165 | 2014 |
| Situation assessment and decision making for lane change assistance using ensemble learning methods Y Hou, P Edara, C Sun Expert Systems with Applications 42 (8), 3875-3882, 2015 | 155 | 2015 |
| Network scale travel time prediction using deep learning Y Hou, P Edara Transportation Research Record 2672 (45), 115-123, 2018 | 82 | 2018 |
| Factors influencing willingness to pool in ride-hailing trips Y Hou, V Garikapati, D Weigl, A Henao, M Moniot, J Sperling Transportation Research Record 2674 (5), 419-429, 2020 | 77 | 2020 |
| In situ investigations on enzymatic degradation of poly (ɛ-caprolactone) Y Hou, J Chen, P Sun, Z Gan, G Zhang Polymer 48 (21), 6348-6353, 2007 | 60 | 2007 |
| A genetic fuzzy system for modeling mandatory lane changing Y Hou, P Edara, C Sun 2012 15th International IEEE Conference on Intelligent Transportation …, 2012 | 57 | 2012 |
| Statistical test for 85th and 15th percentile speeds with asymptotic distribution of sample quantiles Y Hou, C Sun, P Edara Transportation research record 2279 (1), 47-53, 2012 | 57 | 2012 |
| Temperature-Induced Aggregation of Poly(N-isopropylacrylamide)-Stabilized CdS Quantum Dots in Water J Ye, Y Hou, G Zhang, C Wu Langmuir 24 (6), 2727-2731, 2008 | 50 | 2008 |
| Data-driven multi-step demand prediction for ride-hailing services using convolutional neural network C Wang, Y Hou, M Barth Advances in Computer Vision: Proceedings of the 2019 Computer Vision …, 2020 | 43 | 2020 |
| Novel and practical method to quantify the quality of mobility: Mobility energy productivity metric Y Hou, V Garikapati, A Nag, SE Young, T Grushka Transportation Research Record 2673 (10), 141-152, 2019 | 39 | 2019 |
| Reducing ridesourcing empty vehicle travel with future travel demand prediction E Kontou, V Garikapati, Y Hou Transportation Research Part C: Emerging Technologies 121, 102826, 2020 | 37 | 2020 |
| Speed limit effectiveness in short-term rural interstate work zones Y Hou, P Edara, C Sun Transportation Letters: The International Journal of Transportation Research …, 2013 | 32 | 2013 |
| Cost-benefit analysis of sequential warning lights in nighttime work zone tapers. C Sun, P Edara, Y Hou, A Robertson Smart Work Zone Deployment Initiative, 2011 | 26 | 2011 |
| Evaluation of variable advisory speed limits in congested work zones P Edara, C Sun, Y Hou Journal of Transportation Safety & Security 9 (2), 123-145, 2017 | 25 | 2017 |
| Airport analyses informing new mobility shifts: Opportunities to adapt energy-efficient mobility services and infrastructure A Henao, J Sperling, SE Young, V Garikapati, Y Hou National Renewable Energy Lab.(NREL), Golden, CO (United States), 2018 | 21 | 2018 |
| Quantifying the mobility and energy benefits of automated mobility districts using microscopic traffic simulation L Zhu, V Garikapati, Y Chen, Y Hou, HMA Aziz, S Young International Conference on Transportation and Development 2018, 98-108, 2018 | 20 | 2018 |
| Exploring telematics big data for truck platooning opportunities MP Lammert, B Bugbee, Y Hou, M Muratori, J Holden, AW Duran, A Mack, ... National Renewable Energy Lab.(NREL), Golden, CO (United States), 2018 | 19 | 2018 |
| Road network state estimation using random forest ensemble learning Y Hou, P Edara, Y Chang 2017 IEEE 20th International Conference on Intelligent Transportation …, 2017 | 17 | 2017 |
| A modular and transferable reinforcement learning framework for the fleet rebalancing problem E Skordilis, Y Hou, C Tripp, M Moniot, P Graf, D Biagioni IEEE Transactions on Intelligent Transportation Systems 23 (8), 11903-11916, 2021 | 16 | 2021 |
Praveen EdaraUniversity of MissouriVerified email at missouri.edu
