| Exchange rate prediction using hybrid neural networks and trading indicators H Ni, H Yin Neurocomputing 72 (13-15), 2815-2823, 2009 | 127 | 2009 |
| Stock index tracking by Pareto efficient genetic algorithm H Ni, Y Wang Applied Soft Computing 13 (12), 4519-4535, 2013 | 52 | 2013 |
| A self-organising mixture autoregressive network for FX time series modelling and prediction H Ni, H Yin Neurocomputing 72 (16-18), 3529-3537, 2009 | 34 | 2009 |
| Can venture capital trigger innovation? New evidence from China H Ni, T Luan, Y Cao, DC Finlay International Journal of Technology Management 65 (1-4), 189-214, 2014 | 33 | 2014 |
| Self-organising mixture autoregressive model for non-stationary time series modelling H Ni, H Yin International journal of neural systems 18 (06), 469-480, 2008 | 28 | 2008 |
| Multivariate convex support vector regression with semidefinite programming Y Wang, H Ni Knowledge-Based Systems 30, 87-94, 2012 | 22 | 2012 |
| Nowcasting Chinese GDP in a data-rich environment: Lessons from machine learning algorithms Q Zhang, H Ni, H Xu Economic Modelling 122, 106204, 2023 | 18 | 2023 |
| Recurrent self-organising maps and local support vector machine models for exchange rate prediction H Ni, H Yin International Symposium on Neural Networks, 504-511, 2006 | 14 | 2006 |
| Self-Adaptive bagging approach to credit rating N He, W Yongqiao, J Tao, C Zhaoyu Technological Forecasting and Social Change 175, 121371, 2022 | 9 | 2022 |
| Prediction of patent grant and interpreting the key determinants: an application of interpretable machine learning approach L Yao, H Ni Scientometrics 128 (9), 4933-4969, 2023 | 7 | 2023 |
| Generalized self-organizing mixture autoregressive model H Yin, H Ni International Workshop on Self-Organizing Maps, 353-361, 2009 | 6 | 2009 |
| Time-series prediction using self-organising mixture autoregressive network H Ni, H Yin International Conference on Intelligent Data Engineering and Automated …, 2007 | 5 | 2007 |
| Nonparametric bivariate copula estimation based on shape-restricted support vector regression Y Wang, H Ni, S Wang Knowledge-Based Systems 35, 235-244, 2012 | 4 | 2012 |
| Self-Organizing Gaussian Mixture Map Based on Adaptive Recursive Bayesian Estimation. H Ni, Y Wang, B Xu Intelligent Automation & Soft Computing 26 (2), 2020 | 3 | 2020 |
| Multiple-ν support vector regression based on spectral risk measure minimization Y Wang, H Ni, S Wang Neurocomputing 101, 217-228, 2013 | 3 | 2013 |
| Profitability of technical chart pattern trading on FX rates: analyzed by wavelet transform H Ni 2009 Third International Symposium on Intelligent Information Technology …, 2009 | 3 | 2009 |
| A fast self-organizing map algorithm by using genetic selection H Ni 2009 Third International Symposium on Intelligent Information Technology …, 2009 | 3 | 2009 |
| Generalized self-organizing mixture autoregressive model for modeling financial time series H Yin, H Ni Artificial Neural Networks–ICANN 2009: 19th International Conference …, 2009 | 3 | 2009 |
| Forecasting models for the Chinese macroeconomy in a data‐rich environment: Evidence from large dimensional approximate factor models with mixed‐frequency data Q Zhang, H Ni, H Xu Accounting & Finance 63 (1), 719-767, 2023 | 2 | 2023 |
| Consumer credit risk evaluation by logistic regression with self-organizing map H Ni 2010 Sixth International Conference on Natural Computation 1, 205-209, 2010 | 2 | 2010 |
