| Analysis and application of forecasting models in wind power integration: A review of multi-step-ahead wind speed forecasting models J Wang, Y Song, F Liu, R Hou Renewable and Sustainable Energy Reviews 60, 960-981, 2016 | 255 | 2016 |
| Regional concept drift detection and density synchronized drift adaptation A Liu, Y Song, G Zhang, J Lu IJCAI International Joint Conference on Artificial Intelligence, 2017 | 125 | 2017 |
| A hybrid forecasting model based on date-framework strategy and improved feature selection technology for short-term load forecasting P Jiang, F Liu, Y Song Energy 119, 694-709, 2017 | 123 | 2017 |
| A novel model: Dynamic choice artificial neural network (DCANN) for an electricity price forecasting system J Wang, F Liu, Y Song, J Zhao Applied Soft Computing 48, 281-297, 2016 | 102 | 2016 |
| Development of a hybrid model to predict construction and demolition waste: China as a case study Y Song, Y Wang, F Liu, Y Zhang Waste Management 59, 350-361, 2017 | 92 | 2017 |
| The forecasting research of early warning systems for atmospheric pollutants: A case in Yangtze River Delta region Y Song, S Qin, J Qu, F Liu Atmospheric Environment 118, 58-69, 2015 | 91 | 2015 |
| Data-driven decision support under concept drift in streamed big data J Lu, A Liu, Y Song, G Zhang Complex & intelligent systems 6 (1), 157-163, 2020 | 75 | 2020 |
| Interval forecasts of a novelty hybrid model for wind speeds S Qin, F Liu, J Wang, Y Song Energy Reports 1, 8-16, 2015 | 61 | 2015 |
| Spatial-temporal analysis and projection of extreme particulate matter (PM10 and PM2. 5) levels using association rules: A case study of the Jing-Jin-Ji region, China S Qin, F Liu, C Wang, Y Song, J Qu Atmospheric Environment 120, 339-350, 2015 | 60 | 2015 |
| Fuzzy clustering-based adaptive regression for drifting data streams Y Song, J Lu, H Lu, G Zhang IEEE Transactions on Fuzzy Systems 28 (3), 544-557, 2019 | 54 | 2019 |
| Elastic gradient boosting decision tree with adaptive iterations for concept drift adaptation K Wang, J Lu, A Liu, Y Song, L Xiong, G Zhang Neurocomputing 491, 288-304, 2022 | 33 | 2022 |
| Pre-selectable Optical Fingerprints of Heterogeneous Upconversion Nanoparticles J Liao, Jiayan and Zhou, Jiajia and Song, Yiliao and Liu, Baolei and Chen ... Nano Letters, 2021 | 32 | 2021 |
| Cuckoo search-designated fractal interpolation functions with winner combination for estimating missing values in time series P Jiang, F Liu, J Wang, Y Song Applied Mathematical Modelling 40 (23-24), 9692-9718, 2016 | 32 | 2016 |
| A segment-based drift adaptation method for data streams Y Song, J Lu, A Liu, H Lu, G Zhang IEEE transactions on neural networks and learning systems 33 (9), 4876-4889, 2021 | 28 | 2021 |
| Concept drift detection delay index A Liu, J Lu, Y Song, J Xuan, G Zhang IEEE Transactions on Knowledge and Data Engineering 35 (5), 4585-4597, 2022 | 26 | 2022 |
| Learning data streams with changing distributions and temporal dependency Y Song, J Lu, H Lu, G Zhang IEEE Transactions on Neural Networks and Learning Systems 34 (8), 3952-3965, 2021 | 26 | 2021 |
| Learn-to-adapt: Concept drift adaptation for hybrid multiple streams E Yu, Y Song, G Zhang, J Lu Neurocomputing 496, 121-130, 2022 | 20 | 2022 |
| Multiplexed structured illumination super-resolution imaging with lifetime-engineered upconversion nanoparticles B Liu, J Liao, Y Song, C Chen, L Ding, J Lu, J Zhou, F Wang Nanoscale Advances 4 (1), 30-38, 2022 | 18 | 2022 |
| A hybrid multi-step model for forecasting day-ahead electricity price based on optimization, fuzzy logic and model selection P Jiang, F Liu, Y Song Energies 9 (8), 618, 2016 | 16 | 2016 |
| Optical fingerprint classification of single upconversion nanoparticles by deep learning J Liao, J Zhou, Y Song, B Liu, J Lu, D Jin The Journal of Physical Chemistry Letters 12 (41), 10242-10248, 2021 | 15 | 2021 |
Jie LU AO, FIEEE, FIFSA, FACS, Austr...Distinguished Professor, Director of Australian Artificial Intelligence InstituteBestätigte E-Mail-Adresse bei uts.edu.au
