Deep learning with long short-term memory neural networks combining wavelet transform and principal component analysis for daily urban water demand forecasting
作者： Baigang Du , Qiliang Zhou , Jun Guo , Shunsheng Guo , Lei Wang
DOI: 10.1016/J.ESWA.2021.114571
关键词:
摘要: … In recent years, one remarkable and promising deep learning algorithm is long short-term memory network (LSTM) which can effectively learn the long-term dependencies in time series …
sci-hub.st 参考文章(52)
Ovidiu Voitcu, Yau Shu Wong, On the construction of a nonlinear recursive predictor Journal of Computational and Applied Mathematics. ,vol. 190, pp. 393- 407 ,(2006) , 10.1016/J.CAM.2004.12.039
Roger L. Olsen, Rick W. Chappell, Jim C. Loftis, Water quality sample collection, data treatment and results presentation for principal components analysis--literature review and Illinois River Watershed case study. Water Research. ,vol. 46, pp. 3110- 3122 ,(2012) , 10.1016/J.WATRES.2012.03.028
Tae Woo Joo, Seoung Bum Kim, Time series forecasting based on wavelet filtering Expert Systems With Applications. ,vol. 42, pp. 3868- 3874 ,(2015) , 10.1016/J.ESWA.2015.01.026
Tsung-Jung Hsieh, Hsiao-Fen Hsiao, Wei-Chang Yeh, Forecasting stock markets using wavelet transforms and recurrent neural networks: An integrated system based on artificial bee colony algorithm soft computing. ,vol. 11, pp. 2510- 2525 ,(2011) , 10.1016/J.ASOC.2010.09.007
Jonathan A. Tepper, Mahmud S. Shertil, Heather M. Powell, On the importance of sluggish state memory for learning long term dependency Knowledge Based Systems. ,vol. 96, pp. 104- 114 ,(2016) , 10.1016/J.KNOSYS.2015.12.024
G. Banjac, M. Vašak, M. Baotić, Adaptable urban water demand prediction system Water Science & Technology: Water Supply. ,vol. 15, pp. 958- 964 ,(2015) , 10.2166/WS.2015.048
Bruno M. Brentan, Edevar Luvizotto Jr., Manuel Herrera, Joaquín Izquierdo, Rafael Pérez-García, Hybrid regression model for near real-time urban water demand forecasting Journal of Computational and Applied Mathematics. ,vol. 309, pp. 532- 541 ,(2017) , 10.1016/J.CAM.2016.02.009
Arnaud de Myttenaere, Boris Golden, Bénédicte Le Grand, Fabrice Rossi, Mean Absolute Percentage Error for regression models Neurocomputing. ,vol. 192, pp. 38- 48 ,(2016) , 10.1016/J.NEUCOM.2015.12.114
Abdusselam Altunkaynak, Mehmet Ozger, Comparison of Discrete and Continuous Wavelet–Multilayer Perceptron Methods for Daily Precipitation Prediction Journal of Hydrologic Engineering. ,vol. 21, pp. 04016014- ,(2016) , 10.1061/(ASCE)HE.1943-5584.0001376
Ping Jiang, Xuejiao Ma, A hybrid forecasting approach applied in the electrical power system based on data preprocessing, optimization and artificial intelligence algorithms Applied Mathematical Modelling. ,vol. 40, pp. 10631- 10649 ,(2016) , 10.1016/J.APM.2016.08.001