| A hybrid-forecasting model based on Gaussian support vector machine and chaotic particle swarm optimization Q Wu Expert Systems with Applications 37 (3), 2388-2394, 2010 | 106 | 2010 |
| A sparse Gaussian process regression model for tourism demand forecasting in Hong Kong Q Wu, R Law, X Xu Expert Systems with Applications 39 (5), 4769-4774, 2012 | 103 | 2012 |
| The forecasting model based on wavelet ν-support vector machine Q Wu Expert Systems with Applications 36 (4), 7604-7610, 2009 | 94 | 2009 |
| Hybrid dual-tree complex wavelet transform and support vector machine for digital multi-focus image fusion B Yu, B Jia, L Ding, Z Cai, Q Wu, R Law, J Huang, L Song, S Fu Neurocomputing 182, 1-9, 2016 | 91 | 2016 |
| Product demand forecasts using wavelet kernel support vector machine and particle swarm optimization in manufacture system Q Wu Journal of computational and applied mathematics 233 (10), 2481-2491, 2010 | 83 | 2010 |
| Detecting fatigue status of pilots based on deep learning network using EEG signals PY Deng, XY Qiu, Z Tang, WM Zhang, LM Zhu, H Ren, GR Zhou, ... IEEE Transactions on Cognitive and Developmental Systems 13 (3), 575-585, 2020 | 67 | 2020 |
| The hybrid forecasting model based on chaotic mapping, genetic algorithm and support vector machine Q Wu Expert Systems with Applications 37 (2), 1776-1783, 2010 | 64 | 2010 |
| Self-paced dynamic infinite mixture model for fatigue evaluation of pilots’ brains EQ Wu, M Zhou, D Hu, L Zhu, Z Tang, XY Qiu, PY Deng, LM Zhu, H Ren IEEE Transactions on Cybernetics 52 (7), 5623-5638, 2020 | 63 | 2020 |
| Power load forecasts based on hybrid PSO with Gaussian and adaptive mutation and Wv-SVM Q Wu Expert Systems with Applications 37 (1), 194-201, 2010 | 63 | 2010 |
| Complex system fault diagnosis based on a fuzzy robust wavelet support vector classifier and an adaptive Gaussian particle swarm optimization Q Wu, R Law Information Sciences 180 (23), 4514-4528, 2010 | 61 | 2010 |
| Nonparametric bayesian prior inducing deep network for automatic detection of cognitive status EQ Wu, D Hu, PY Deng, Z Tang, Y Cao, WM Zhang, LM Zhu, H Ren IEEE Transactions on Cybernetics 51 (11), 5483-5496, 2020 | 49 | 2020 |
| Pilots’ fatigue status recognition using deep contractive autoencoder network EQ Wu, XY Peng, CZ Zhang, JX Lin, RSF Sheng IEEE Transactions on Instrumentation and Measurement 68 (10), 3907-3919, 2019 | 49 | 2019 |
| Hybrid model based on wavelet support vector machine and modified genetic algorithm penalizing Gaussian noises for power load forecasts Q Wu Expert Systems with Applications 38 (1), 379-385, 2011 | 43 | 2011 |
| Classification of EMG signals by BFA-optimized GSVCM for diagnosis of fatigue status Q Wu, C Xi, L Ding, C Wei, H Ren, R Law, H Dong, XL Li IEEE Transactions on Automation Science and Engineering 14 (2), 915-930, 2016 | 40 | 2016 |
| Hybrid BF–PSO and fuzzy support vector machine for diagnosis of fatigue status using EMG signal features Q Wu, JF Mao, CF Wei, S Fu, R Law, L Ding, BT Yu, B Jia, CH Yang Neurocomputing 173, 483-500, 2016 | 39 | 2016 |
| A self-adaptive 1D convolutional neural network for flight-state identification X Chen, F Kopsaftopoulos, Q Wu, H Ren, FK Chang Sensors 19 (2), 275, 2019 | 38 | 2019 |
| A forecasting model based support vector machine and particle swarm optimization Q Wu, HS Yan, HB Yang 2008 Workshop on power electronics and intelligent transportation system …, 2008 | 37 | 2008 |
| Detecting dynamic behavior of brain fatigue through 3-d-CNN-LSTM EQ Wu, P Xiong, ZR Tang, GJ Li, A Song, LM Zhu IEEE Transactions on Systems, Man, and Cybernetics: Systems 52 (1), 90-100, 2021 | 36 | 2021 |
| A hybrid-forecasting model reducing Gaussian noise based on the Gaussian support vector regression machine and chaotic particle swarm optimization Q Wu, R Law, E Wu, J Lin Information Sciences 238, 96-110, 2013 | 36 | 2013 |
| Cauchy mutation based on objective variable of Gaussian particle swarm optimization for parameters selection of SVM Q Wu, R Law Expert Systems with Applications 38 (6), 6405-6411, 2011 | 35 | 2011 |
