| ARMA based approaches for forecasting the tuple of wind speed and direction E Erdem, J Shi Applied Energy 88 (4), 1405-1414, 2011 | 905 | 2011 |
| On comparing three artificial neural networks for wind speed forecasting G Li, J Shi Applied Energy 87 (7), 2313-2320, 2010 | 850 | 2010 |
| Fine tuning support vector machines for short-term wind speed forecasting J Zhou, J Shi, G Li Energy Conversion and Management 52 (4), 1990-1998, 2011 | 407 | 2011 |
| RFID localization algorithms and applications—a review J Zhou, J Shi Journal of intelligent manufacturing 20, 695-707, 2009 | 361 | 2009 |
| Evaluation of hybrid forecasting approaches for wind speed and power generation time series J Shi, J Guo, S Zheng Renewable and Sustainable Energy Reviews 16 (5), 3471-3480, 2012 | 291 | 2012 |
| Bayesian adaptive combination of short-term wind speed forecasts from neural network models G Li, J Shi, J Zhou Renewable Energy 36 (1), 352-359, 2011 | 264 | 2011 |
| Modeling methods for GenCo bidding strategy optimization in the liberalized electricity spot market–A state-of-the-art review G Li, J Shi, X Qu Energy 36 (8), 4686-4700, 2011 | 252 | 2011 |
| Comprehensive evaluation of ARMA–GARCH (-M) approaches for modeling the mean and volatility of wind speed H Liu, E Erdem, J Shi Applied Energy 88 (3), 724-732, 2011 | 239 | 2011 |
| Applying ARMA–GARCH approaches to forecasting short-term electricity prices H Liu, J Shi Energy Economics 37, 152-166, 2013 | 222 | 2013 |
| Comprehensive evaluation of wind speed distribution models: A case study for North Dakota sites J Zhou, E Erdem, G Li, J Shi Energy Conversion and Management 51 (7), 1449-1458, 2010 | 215 | 2010 |
| The influence of material models on finite element simulation of machining J Shi, CR Liu J. Manuf. Sci. Eng. 126 (4), 849-857, 2004 | 142 | 2004 |
| Additive manufacturing of zirconia ceramics: A state-of-the-art review X Zhang, X Wu, J Shi Journal of materials research and technology 9 (4), 9029-9048, 2020 | 124 | 2020 |
| Prediction of wind speed time series using modified Taylor Kriging method H Liu, J Shi, E Erdem Energy 35 (12), 4870-4879, 2010 | 123 | 2010 |
| Application of Bayesian model averaging in modeling long-term wind speed distributions G Li, J Shi Renewable Energy 35 (6), 1192-1202, 2010 | 111 | 2010 |
| Agent-based modeling for trading wind power with uncertainty in the day-ahead wholesale electricity markets of single-sided auctions G Li, J Shi Applied Energy 99, 13-22, 2012 | 104 | 2012 |
| On predicting chip morphology and phase transformation in hard machining J Shi, CR Liu The International Journal of Advanced Manufacturing Technology 27, 645-654, 2006 | 98 | 2006 |
| Rescheduling of elective patients upon the arrival of emergency patients E Erdem, X Qu, J Shi Decision Support Systems 54 (1), 551-563, 2012 | 94 | 2012 |
| Comparison of bivariate distribution construction approaches for analysing wind speed and direction data E Erdem, J Shi Wind Energy 14 (1), 27-41, 2011 | 89 | 2011 |
| Influence of laser power and scanning strategy on residual stress distribution in additively manufactured 316L steel P Bian, J Shi, Y Liu, Y Xie Optics & Laser Technology 132, 106477, 2020 | 88 | 2020 |
| Perspective of additive manufacturing for metamaterials development X Wu, Y Su, J Shi Smart Materials and Structures 28 (9), 093001, 2019 | 88 | 2019 |
