Daci Lab dedicates to generate cutting-edge research findings on intersections between data science and multiple selected domains including but not limited to the renewable energy, energy management, industrial Internet-of-Things (IoT), as well as system prognostics and health management (PHM).
Publications
Journal articles
[1] Z. Zheng, Z. Zhang*, L. Wang, and X. Luo, "Denoising Temporal Convolutional Recurrent Autoencoders for Time Series Classification," Information Sciences, 2021, In press. (Data Science)
[2] L. Yang and Z. Zhang*, "A Deep Attention Convolutional Recurrent Network Assisted by K-shape Clustering and Enhanced Memory for Short Term Wind Speed Predictions," IEEE Transactions on Sustainable Energy, 2021, In press. (Data Science in Renewable Energy)
[3] T. Wang, Z. Zhang*, F. Yang, and K. L. Tsui, "Automatic Rail Component Detection Based on AttnConv-net," IEEE Sensors Journal, 2021, In press. (Data Science in Railway System PHM)
[4] L. Yang, Z. Zheng, and Z. Zhang*, "An Improved Mixture Density Network via Wasserstein Distance Based Adversarial Learning for Probabilistic Wind Speed Predictions," IEEE Transactions on Sustainable Energy, 2021, In press. (Data Science in Renewable Energy)
[5] L. Yang, L. Wang*, Z. Zheng, and Z. Zhang*, "A Continual Learning-based Framework for Developing A Single Wind Turbine Cybertwin Adaptively Serving Multiple Modeling Tasks," IEEE Transactions on Industrial Informatics, 2021, In press. (Data Science in Renewable Energy)
[6] L. Zhuang, H. Qi, and Z. Zhang*, "The Automatic Rail Surface Multi-flaw Identification Based on A Deep Learning Powered Framework," IEEE Transactions on Intelligent Transportation Systems, 2021, In press. (Data Science in Railway System PHM)
[7] Z. Zheng, L. Wang, L. Yang, and Z. Zhang*, "Generative Probabilistic Wind Speed Forecasting: A Variational Recurrent Autoencoder Based Method," IEEE Transactions on Power Systems, 2021, In press. (Data Science in Renewable Energy)
[8] Z. Mo, Z. Zhang*, and K. L. Tsui, "The Variational Kernel Based 1-D Convolutional Neural Network for Machinery Fault Diagnosis," IEEE Transactions on Instrumentation and Measurement, Vol. 70, Article ID: 3523210, 2021. (Data Science in System PHM)
[9] B. Zhang and Z. Zhang*, "A Robust Model for Scheduling Power Productions of Multiple Offshore Wind Farms Using One-to-many Maintenance Services," IET Renewable Power Generation, Vol. 15, No. 13, pp. 2997-3013, 2021. (Renewable Energy)
[10] Z. Zheng, H. Qi, L. Zhuang*, and Z. Zhang*, "Automated Rail Surface Crack Analytics Using Deep Data-driven Models and Transfer Learning," Sustainable Cities and Society, Vol. 70, Article ID: 102898, 2021. (Data Science in Railway System PHM)
[11] Z. Wang, L. Wang*, C. Huang, Z. Zhang, and X. Luo, "Soil Moisture Sensor-based Automated Soil Water Content Cycle Classification with a Hybrid Symbolic Aggregate Approximation Algorithm," IEEE Internet of Things Journal, Vol. 8, No. 18, pp. 14003-14012, 2021. (Data Science and IoT)
[12] X. Liu, L. Yang, and Z. Zhang*, "Short-term Multi-step Ahead Wind Power Predictions Based on A Novel Deep Convolutional Recurrent Network Method," IEEE Transactions on Sustainable Energy, Vol. 12, No. 3, pp. 1820-1833, 2021. (Data Science in Renewable Energy).
[13] B. Zhang and Z. Zhang*, "A Two-Stage Model for Asynchronously Scheduling Offshore Wind Farm Maintenance Tasks and Power Productions," International Journal of Electrical Power and Energy Systems, Vol. 130, Article ID: 107013, 2021 (Renewable Energy)
[14] Z. Fei, F. Yang*, K. L. Tsui, L. Li, and Z. Zhang, "Early prediction of battery lifetime via a machine learning based framework," Energy, Vol. 225, Article ID: 120205, 2021 (Data Science in Battery Systems)
[15] X. Liu and Z. Zhang*, "A Two-stage Deep Autoencoder Based Missing Data Imputation Method for Wind Farm SCADA Data," IEEE Sensors Journal, Vol. 21, No. 9, pp. 10933-10945, 2021. (Data Science in Renewable Energy)
[16] H. Qiao, Z. Zhang*, and Q. Su, "The optimal hourly electricity price considering wind electricity uncertainty based on conditional value at risk," International Journal of Green Energy, Vol. 18, No. 5, pp. 512-524, 2021. (Data Science in Power and Energy)
[17] L. Yang and Z. Zhang*, "Wind Turbine Gearbox Failure Detection Based on SCADA Data: A Deep Learning Based Approach," IEEE Transactions on Instrumentation and Measurement, Vol. 70, Article ID: 3507911, 2021. (Data Science in Renewable Energy)
[18] X. Liu, Z. Cao, and Z. Zhang*, "Short-term Predictions of Multiple Wind Turbine Power Outputs Based on Deep Neural Networks with Transfer Learning," Energy, Vol. 217, Article ID: 119356, 2021. (Data Science in Renewable Energy)
[19] J. Chen, Z. Zhang*, and F. Wu, "A Data-driven Method for Enhancing the Image-based Automatic Inspection of IC Wire Bonding Defects," International Journal of Production Research, Vol. 59, No. 16, pp. 4779-4793, 2021. (Data Science in Intelligent Manufacturing)
[20] M. Ghosh, Y. Li, L. Zeng, Z. Zhang, and Q. Zhou*, "Modeling multivariate profiles using Gaussian process-controlled B-splines," IISE Transactions, Vol. 53, No. 7, pp. 787-798, 2021. (Data Science in System PHM)
[21] L. Yang and Z. Zhang*, "A Conditional Convolutional Autoencoder Based Method for Monitoring Wind Turbine Blade Breakages," IEEE Transactions on Industrial Informatics, Vol. 17, No. 9, pp. 6390-6398, 2021. (Data Science in Renewable Energy)
[22] L. Zhuang, Z. Zhang*, and L. Wang, "The Automatic Segmentation of Residential Solar Panels Based on Satellite Images: A Cross Learning Driven U-Net Method," Applied Soft Computing, Vol. 92, Article ID: 106283, 2020. (Data Science in Renewable Energy)
[23] C. Huang, L. Wang, Z. Zhang*, and X. Luo, "The Point and Interval Forecasting of Solar Irradiance with an Active Gaussian Process," IET Renewable Power Generation, Vol. 14, No. 6, pp. 1020-1030, 2020. (Data Science in Renewable Energy)
[24] X. Liu, Z. Zhang*, and Z. Song, "A comparative study of the data-driven day-ahead hourly provincial load forecasting methods: From classical data mining to deep learning," Renewable and Sustainable Energy Reviews, Vol. 119, Article ID: 109632, 2020. (Data Science in Power and Energy)
[25] Z. Cao, C. Wan*, Z. Zhang, F. Li, and Y. Song, "Hybrid Ensemble Deep Learning for Deterministic and Probabilistic Low-voltage Load Forecasting," IEEE Transactions on Power Systems, Vol. 35, No. 3, pp. 1881-1897, 2020. (Data Science in Power and Energy)
[26] C. Huang, L. Wang, Z. Zhang*, R. Yeung, A. Bensoussan, and H. Chung, "A Novel Spline Model Guided Maximum Power Point Tracking Method for Photovoltaic Systems," IEEE Transactions on Sustainable Energy, Vol. 11, No. 3, pp. 1309-1322, 2020. (Data Science in Renewable Energy)
[27] Z. Tang and Z. Zhang*, "The Multi-objective Optimization of Combustion System Operations Based on Deep Data-driven Models," Energy, Vol. 182, pp. 37-47, 2019. (Data Science in Power and Energy)
[28] J. Zhu, Y. Shen, Z. Song*, D. Zhou, Z. Zhang, and A. Kusiak, "Data-driven Building Load Profiling and Energy Management," Sustainable Cities and Society, Vol. 49, Article ID: 101587, 2019. (Data Science in Power and Energy)
[29] L. Wang, Z. Zhang*, and X. Luo, "A Two-stage Data-driven Approach for Image based Wind Turbine Blade Crack Inspections," IEEE-ASME Transactions on Mechatronics, Vol. 24, No. 3, pp. 1271-1281, 2019. (Data Science in Renewable Energy)
[30] L. Wang, L. Zhuang, and Z. Zhang*, "Automatic Detection of Rail Surface Crack with a Superpixel-based Data-driven Framework," ASCE Journal of Computing in Civil Engineering, Vol. 33, No. 1, pp. 04018053: 1-9, 2019. (Data Science in Railway System PHM)
[31] J. Man, Z. Zhang*, and Q. Zhou, "Data-driven predictive analytics of unexpected wind turbine shut-downs," IET Renewable Power Generation, Vol. 12, No. 15, pp. 1833-1842, 2018. (Data Science in Renewable Energy)
[32] X. Luo*, J. Sun, L. Wang, W. Wang, W. Zhao, J. Wu, J.H. Wang, and Z. Zhang, "Short-term Wind Speed Forecasting via Stacked Extreme Learning Machine With Generalized Correntropy," IEEE Transactions on Industrial Informatics, Vol. 14, No. 11, pp. 4963-4971, 2018. (Data Science in Renewable Energy)
[33] L. Zhuang, L. Wang, Z. Zhang*, and K. L. Tsui, "Automated vision inspection of rail surface cracks: A double-layer data-driven framework," Transportation Research Part C: Emerging Technologies, Vol. 92, pp. 258-277, 2018. (Data Science in Railway System PHM)
[34] Z. Song*, Z. Zhang, Y. Jiang, and J. Zhu, "Wind Turbine Health State Monitoring Based on a Bayesian Data-driven Approach," Renewable Energy, Vol. 125, pp. 172-181, 2018. (Data Science in Renewable Energy)
[35] H. Long, Z. Zhang*, M. Sun, and Y. Li, "The Data-driven Schedule of Wind Farm Power Generations and Required Reserves," Energy, Vol. 149, pp. 485-495, 2018. (Data Science in Renewable Energy)
[36] L. Wang, Z. Zhang*, C. Huang, and K. L. Tsui, "A GPU-accelerated Parallel Jaya Algorithm for Efficiently Estimating Li-ion Battery Model Parameters," Applied Soft Computing, Vol. 65, pp. 12-20, 2018. (Data Science in Battery Systems)
[37] Y. Wang*, H. Liu, H. Long, Z. Zhang, and S. Yang, "Differential evolution with a new encoding mechanism for optimizing wind farm layout," IEEE Transactions on Industrial Informatics, Vol. 14, No. 3, pp. 1040-1054, 2018. (Renewable Energy)
[38] C. Huang, L. Wang, R. Yeung, Z. Zhang*, H. Chung, and A. Bensoussan, "A Prediction Model Guided Jaya Algorithm for the PV System Maximum Power Point Tracking," IEEE Transactions on Sustainable Energy, Vol. 9, No. 1, pp. 45-55, 2018. (Data Science in Renewable Energy)
[39] L. Wang, Z. Zhang*, J. Xu, and R. Liu, "Wind Turbine Blade Breakage Monitoring with Deep Autoencoders," IEEE Transactions on Smart Grid, Vol. 9, No. 4, pp. 2824-2833, 2018. (Data Science in Renewable Energy)
[40] Y. Jiang, H. Long*, Z. Zhang*, and Z. Song, "Day-ahead Prediction of Bi-hourly Solar Radiance with a Markov Switch Approach," IEEE Transactions on Sustainable Energy, Vol. 8, No. 4, pp. 1536-1547, 2017. (Data Science in Renewable Energy)
[41] L. Wang and Z. Zhang*, "Automatic Detection of Wind Turbine Blade Surface Cracks Based on UAV-taken Images," IEEE Transactions on Industrial Electronics, Vol. 64, No. 9, pp. 7293-7303, 2017. (Data Science in Renewable Energy)
[42] H. Long, Z. Zhang*, Z. Song, and A. Kusiak, "Formulation and Analysis of Grid and Coordinate Models for Planning Wind Farm Layouts," IEEE Access, Vol. 5, pp. 1810-1819, 2017. (Renewable Energy)
[43] L. Wang, Z. Zhang*, and J. Chen, "Short-Term Electricity Price Forecasting with Stacked Denoising Autoencoders," IEEE Transactions on Power Systems, Vol. 32, No. 4, pp. 2673-2681, 2017. (Data Science in Power and Energy)
[44] L. Wang, Z. Zhang*, H. Long, J. Xu, and R. Liu, "Wind Turbine Gearbox Failure Identification with Deep Neural Networks," IEEE Transactions on Industrial Informatics, Vol. 13, No. 3, pp. 1360-1368, 2017. (Data Science in Renewable Energy)
[45] H. Long, M. Eghlimi, and Z. Zhang*, "Configuration Optimization and Analysis of a Large Scale PV/wind System," IEEE Transactions on Sustainable Energy, Vol. 8, No. 1, pp. 84-93, 2017. (Renewable Energy)
[46] Z. Zhang, A. Kusiak, Y. Zeng, and X. Wei*, "Modeling and optimization of a wastewater pumping system with data-mining methods," Applied Energy, Vol. 164, pp. 303-311, 2016. (Data Science in Energy Saving)
[47] M. Tan and Z. Zhang*, "Wind Turbine Modeling with Data-driven Methods and Radially Uniform Designs," IEEE Transactions on Industrial Informatics, Vol. 12, No. 3, pp. 1261-1269, 2016. (Data Science in Renewable Energy)
[48] C. Sun, Z. Bie, and Z. Zhang*, "A new framework for the wind power curtailment and absorption evaluation," International Transactions on Electrical Energy Systems, Vol. 26, No. 10, pp. 2134-2147, 2016. (Renewable Energy)
[49] Z. Song, Z. Zhang*, and X. Chen "The decision model of 3-dimensional wind farm layout design," Renewable Energy, Vol. 85, pp. 248-258, 2016. (Renewable Energy)
[50] Y. Zeng, Z. Zhang, A. Kusiak, F. Tang, and X. Wei*, "Optimizing wastewater pumping system with data-driven models and a greedy electromagnetism-like algorithm," Stochastic Environmental Research and Risk Assessment, Vol. 30, No. 4, pp, 1263-1275, 2016. (Data Science in Energy Saving)
[51] Z. Zhang*, X. He, and A. Kusiak, "Data-driven minimization of pump operating and maintenance cost," Engineering Applications of Artificial Intelligence, Vol. 40, pp. 37-46, 2015. (Data Science in Energy Saving)
[52] H. Long, L. Wang, Z. Zhang, Z. Song, and J. Xu, "Data-Driven Wind Turbine Power Generation Performance Monitoring," IEEE Transactions on Industrial Electronics, Vol. 62, No. 10, pp. 6627-6635, 2015. (Data Science in Renewable Energy)
[53] Y. Zeng, Z. Zhang*, and A. Kusiak, "Predictive modeling and optimization of a multi-zone HVAC system with data mining and firefly algorithms," Energy, Vol. 85, pp. 393-402, 2015. (Data Science in Energy Saving)
[54] H. Long and Z. Zhang*, "A Two-Echelon Wind Farm Layout Planning Model," IEEE Transactions on Sustainable Energy, Vol. 6, No. 3, pp. 863-871, 2015. (Renewable Energy)
[55] H. Long, Z. Zhang*, and Y. Su, "Analysis of daily solar power prediction with data-driven approaches," Applied Energy, Vol. 126, pp. 29-37, 2014. (Data Science in Renewable Energy)
[56] X. He, Z. Zhang, and A. Kusiak*, "Performance Optimization of HVAC Systems with Computational Intelligence Algorithms," Energy and Buildings, Vol. 81, pp. 371-380, 2014. (Data Science in Energy Saving)
[57] A. Kusiak*, G. Xu, and Z. Zhang, "Minimization of energy consumption in HVAC systems with data-driven models and an interior-point method," Energy Conversion and Management, Vol. 85, pp. 146-153, 2014. (Data Science in Energy Saving)
[58] Z. Song, Y. Jiang*, and Z. Zhang, "Short-term Wind Speed Forecasting with Markov-switching Model," Applied Energy, Vol. 130, pp. 103-112, 2014. (Data Science in Renewable Energy)
[59] Z. Zhang, Q. Zhou, and A. Kusiak*, "Optimization of Wind Power and Its Variability With a Computational Intelligence Approach," IEEE Transactions on Sustainable Energy, Vol. 5, No. 1, pp. 228-236, 2014. (Data Science in Renewable Energy)
[60] A. Kusiak*, Z. Zhang, and A. Verma, "Prediction, operations, and condition monitoring in wind energy," Energy, Vol. 60, pp. 1-12, 2013. (Renewable Energy)
[61] A. Verma, Z. Zhang, and A. Kusiak*, "Modeling and Prediction of Gearbox Faults With Data-Mining Algorithms," ASME Journal of Solar Energy Engineering, Vol. 135, No. 3, pp. 031007: 1-11, 2013. (Data Science in Renewable Energy)
[62] A. Kusiak*, Y. Zeng, and Z. Zhang, "Modeling and analysis of pumps in a wastewater treatment plant: A data-mining approach," Engineering Applications of Artificial Intelligence, Vol. 26, No. 7, pp. 1643-1651, 2013. (Data Science in System Modeling)
[63] Z. Zhang, A. Kusiak, and Z. Song*, "Scheduling electric power production at a wind farm," European Journal of Operational Research, Vol. 224, No. 1, pp. 227-238, 2013. (Renewable Energy)
[64] A. Kusiak*, Z. Zhang, and G. Xu, "Minimization of Wind Farm Operational Cost Based on Data-driven Models," IEEE Transactions on Sustainable Energy, Vol. 4, No. 3, pp. 756-764, 2013. (Data Science in Renewable Energy)
[65] Z. Zhang, Y. Zeng, and A. Kusiak*, "Minimizing pump energy in a wastewater processing plant," Energy, Vol. 47, No. 1, pp. 505-514, 2012 (Data Science in Energy Saving)
[66] A. Kusiak* and Z. Zhang, "Control of wind turbine power and vibration with a data-driven approach," Renewable Energy, Vol. 43, pp. 73-82, 2012. (Data Science in Renewable Energy)
[67] Z. Zhang, A. Verma, and A. Kusiak*, "Fault Analysis and Condition Monitoring of the Wind Turbine Gearbox," IEEE Transactions on Energy Conversion, Vol. 27, No. 2, pp. 526-535, 2012. (Renewable Energy)
[68] Z. Zhang and A. Kusiak*, "Monitoring wind turbine vibration based on SCADA data," ASME Journal of Solar Energy Engineering, Vol. 134, No. 2, pp. 021004: 1-12, 2012. (Data Science in Renewable Energy)
[69] Z. Zhang and A. Kusiak*, "Modeling for Optimization of Energy Consumption of Pumps in a Wastewater Processing Plant," ASCE Journal of Energy Engineering, Vol. 137, No. 4, pp. 159-168, 2011. (Data Science in System Modeling)
[70] A. Kusiak*, H. Zheng, and Z. Zhang, "Virtual wind speed sensor for wind turbines," ASCE Journal of Energy Engineering, Vol. 137, No. 2, pp. 59-69, 2011. (Data Science in Renewable Energy)
[71] A. Kusiak* and Z. Zhang, "Adaptive control of a wind turbine with data mining and swarm intelligence," IEEE Transactions on Sustainable Energy, Vol. 2, No. 1, pp. 28-36, 2011. (Data Science in Renewable Energy)
[72] A. Kusiak* and Z. Zhang, "Short-horizon prediction of wind power: A data-driven approach," IEEE Transactions on Energy Conversion, Vol. 25, No. 4, pp. 1112-1122, 2010. (Data Science in Renewable Energy)
[73] A. Kusiak* and Z. Zhang, "Analysis of wind turbine vibrations based on SCADA data," ASME Journal of Solar Energy Engineering, Vol. 132, No. 3, pp. 031008, 2010. (Data Science in Renewable Energy)
[74] A. Kusiak*, Z. Zhang, and M. Li, "Optimization of wind turbine performance with data-driven models," IEEE Transactions on Sustainable Energy, Vol. 1, No. 2, pp. 66-76, 2010. (Data Science in Renewable Energy)
[75] A. Kusiak*, M. Li, and Z. Zhang, "A data-driven approach for steam load prediction in buildings," Applied Energy, Vol. 87, No. 3, pp. 925-933, 2010. (Data Science in System Modeling)
Book Chapters
[1] K. L. Tsui, Y. Zhao, and Z. Zhang, "Graphical Big Data: From Simulation to Immersive Visualization," in Creative and Collaborative Learning through Immersion: Interdisciplinary and International Perspectives, Editors: A. Hui and C. Wagner, Springer, 2021.
Refereed Conference Papers
[1] X. Liu, Z. Zheng, Z. Zhang, and Z. Cao, "A statistical learning framework for the intelligent imputation of offshore wind farm missing scada data," 8th Renewable Power Generation Conference (RPG 2019), Oct. 2019, Institution of Engineering and Technology.
[2] L. Zhuang, L. Wang, and Z. Zhang, "Automated vision inspection of rail surface cracks: A double-layer data-driven framework," Dec 2018, 48th International Conference on Computers & Industrial Engineering 2018 (CIE48). Xu, X., Dessouky, M. I. & Zhong, R. Y. (eds.). Computers and Industrial Engineering, Vol. 2. p. 1187 (Proceedings of International Conference on Computers and Industrial Engineering, CIE).
[3] C. Huang, Z. Zhang, L. Wang, Z. Song, and H. Long, "A Novel Global Maximum Power Point Tracking Method for PV System Using Jaya Algorithm," Nov 2017, 2017 IEEE Conference on Energy Internet and Energy System Integration (EI2) . IEEE, p. 1-5 (2017 IEEE Conference on Energy Internet and Energy System Integration, EI2 2017 - Proceedings; vol. 2018-January).
[4] H. Nguyen, X. Sun, Z. Zhang, and M. Li, "Real-time health monitoring of wind turbine gearbox performance," May 2017, Proceedings of the 2017 Industrial and Systems Engineering Conference. Institute of Industrial and Systems Engineers (IISE), p. 1091-1096.
[5] C. Huang, Z. Zhang, and A. Bensoussan, "Forecasting of daily global solar radiation using wavelet transform-coupled Gaussian process regression: Case study in Spain," 22 Dec 2016, 2016 IEEE INNOVATIVE SMART GRID TECHNOLOGIES - ASIA (ISGT-ASIA). IEEE, p. 799-804 7796487.
[6] L. Wang, H. Long, Z. Zhang, J. Xu, and R. Liu, "Wind turbine gearbox failure monitoring based on SCADA data analysis," 10 Nov 2016, IEEE Power and Energy Society General Meeting. IEEE, Vol. 2016-November. 7741571.
[7] K. Ahad Esmaeili, M. Eghlimi, Z. Zhang, "Forecasting the Electricity Price in Iran Power Market: A Comparison between Neural Networks and Time Series Methods," IEEE APPEEC 2014, 2014, pp. 1-6.
[8] A. Kusiak and Z. Zhang, "Optimization of Power and its Variability with an Artificial Immune Network Algorithm," Power Systems Conference and Exposition (PSCE), 2011 IEEE/PES, March 2011, pp. 1-8.
Magazines
[1] A. Kusiak and Z. Zhang, "Gearbox Fault Detection," Wind Systems Magazine, Vol. 3, No. 33, pp. 54-59, 2012.
[2] A. Kusiak and Z. Zhang, "Near Term Power Prediction," Wind Systems Magazine, Vol. 2, No. 14, pp. 48-53, 2010.
Patents
[1] X. Liu and Z. Zhang, A System And Method for Monitoring A Device, US Patent, 2019, Priority No. 16/592,815.