| Practical genetic algorithms RL Haupt, SE Haupt John Wiley & Sons, 2004 | 7289 | 2004 |
| Using artificial intelligence to improve real-time decision-making for high-impact weather A McGovern, KL Elmore, DJ Gagne, SE Haupt, CD Karstens, R Lagerquist, ... Bulletin of the American Meteorological Society 98 (10), 2073-2090, 2017 | 213 | 2017 |
| WRF-Solar: Description and clear-sky assessment of an augmented NWP model for solar power prediction PA Jimenez, JP Hacker, J Dudhia, SE Haupt, JA Ruiz-Arias, ... Bulletin of the American Meteorological Society 97 (7), 1249-1264, 2016 | 153* | 2016 |
| Artificial intelligence methods in the environmental sciences SE Haupt, A Pasini, C Marzban Springer Science & Business Media, 2008 | 148 | 2008 |
| Solar forecasting: methods, challenges, and performance A Tuohy, J Zack, SE Haupt, J Sharp, M Ahlstrom, S Dise, E Grimit, ... IEEE Power and Energy Magazine 13 (6), 50-59, 2015 | 143 | 2015 |
| A wind power forecasting system to optimize grid integration WP Mahoney, K Parks, G Wiener, Y Liu, WL Myers, J Sun, ... IEEE Transactions on Sustainable Energy 3 (4), 670-682, 2012 | 139 | 2012 |
| Improving pollutant source characterization by better estimating wind direction with a genetic algorithm CT Allen, GS Young, SE Haupt Atmospheric Environment 41 (11), 2283-2289, 2007 | 100 | 2007 |
| A demonstration of coupled receptor/dispersion modeling with a genetic algorithm SE Haupt Atmospheric Environment 39 (37), 7181-7189, 2005 | 93 | 2005 |
| Storm-based probabilistic hail forecasting with machine learning applied to convection-allowing ensembles DJ Gagne, A McGovern, SE Haupt, RA Sobash, JK Williams, M Xue Weather and forecasting 32 (5), 1819-1840, 2017 | 90 | 2017 |
| Recent trends in variable generation forecasting and its value to the power system KD Orwig, ML Ahlstrom, V Banunarayanan, J Sharp, JM Wilczak, ... IEEE Transactions on Sustainable Energy 6 (3), 924-933, 2014 | 83 | 2014 |
| Short-term wind forecast of a data assimilation/weather forecasting system with wind turbine anemometer measurement assimilation WYY Cheng, Y Liu, AJ Bourgeois, Y Wu, SE Haupt Renewable Energy 107, 340-351, 2017 | 80 | 2017 |
| Validation of a receptor–dispersion model coupled with a genetic algorithm using synthetic data SE Haupt, GS Young, CT Allen Journal of applied meteorology and climatology 45 (3), 476-490, 2006 | 77 | 2006 |
| Source characterization with a genetic algorithm–coupled dispersion–backward model incorporating SCIPUFF CT Allen, SE Haupt, GS Young Journal of applied meteorology and climatology 46 (3), 273-287, 2007 | 75 | 2007 |
| A preliminary study of assimilating numerical weather prediction data into computational fluid dynamics models for wind prediction FJ Zajaczkowski, SE Haupt, KJ Schmehl Journal of Wind Engineering and Industrial Aerodynamics 99 (4), 320-329, 2011 | 74 | 2011 |
| The continuous genetic algorithm. Practical genetic algorithms RL Haupt, SE Haupt John Wiley & Sons, Inc, 2004 | 71* | 2004 |
| Interpretable deep learning for spatial analysis of severe hailstorms DJ Gagne II, SE Haupt, DW Nychka, G Thompson Monthly Weather Review 147 (8), 2827-2845, 2019 | 69 | 2019 |
| An empirical model of barotropic atmospheric dynamics and its response to tropical forcing G Branstator, SE Haupt Journal of Climate 11 (10), 2645-2667, 1998 | 66 | 1998 |
| Variable generation power forecasting as a big data problem SE Haupt, B Kosović IEEE Transactions on Sustainable Energy 8 (2), 725-732, 2016 | 64 | 2016 |
| UAV navigation by an expert system for contaminant mapping with a genetic algorithm Y Kuroki, GS Young, SE Haupt Expert Systems with Applications 37 (6), 4687-4697, 2010 | 60 | 2010 |
| Assessing sensitivity of source term estimation KJ Long, SE Haupt, GS Young Atmospheric environment 44 (12), 1558-1567, 2010 | 60 | 2010 |
