Improving the accuracy of prediction of PM10 pollution by the wavelet transformation and an ensemble of neural predictors
暂无分享,去创建一个
[1] S. Vitabile,et al. Two-days ahead prediction of daily maximum concentrations of SO2, O3, PM10, NO2, CO in the urban area of Palermo, Italy , 2007 .
[2] Saleh M. Al-Alawi,et al. Combining principal component regression and artificial neural networks for more accurate predictions of ground-level ozone , 2008, Environ. Model. Softw..
[3] C. L. Nikias,et al. Higher-order spectra analysis : a nonlinear signal processing framework , 1993 .
[4] Anastasia K Paschalidou,et al. Forecasting hourly PM10 concentration in Cyprus through artificial neural networks and multiple regression models: implications to local environmental management , 2011, Environmental science and pollution research international.
[5] Silas Michaelides,et al. Spatial distribution of some dynamic parameters during the evolution of selected depressions over the area of Cyprus , 2004 .
[6] Simon Haykin,et al. Neural Networks: A Comprehensive Foundation , 1998 .
[7] Giorgio Corani,et al. Air quality prediction in Milan: feed-forward neural networks, pruned neural networks and lazy learning , 2005 .
[8] Ingrid Daubechies,et al. Ten Lectures on Wavelets , 1992 .
[9] Kamaruzzaman Sopian,et al. Application of Wavelet Transform on Airborne Suspended Particulate Matter and Meteorological Temporal Variations , 2008 .
[10] Krzysztof Siwek,et al. Neural predictor ensemble for accurate forecasting of PM10 pollution , 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).
[11] Stanislaw Osowski,et al. Forecasting of the daily meteorological pollution using wavelets and support vector machine , 2007, Eng. Appl. Artif. Intell..
[12] Krzysztof Siwek,et al. Ensemble of Predictors for Forecasting the PM10 Pollution , 2009 .
[13] Fachao Qin,et al. Variations of PM10 Pollution Index in Shanghai during Recent 9 Years , 2010, 2010 International Conference on Challenges in Environmental Science and Computer Engineering.
[14] Philip Demokritou,et al. Measurements of PM10 and PM2.5 particle concentrations in Athens, Greece , 2003 .
[15] Ludmila I. Kuncheva,et al. Combining Pattern Classifiers: Methods and Algorithms , 2004 .
[16] Gavin C. Cawley,et al. Extensive evaluation of neural network models for the prediction of NO2 and PM10 concentrations, compared with a deterministic modelling system and measurements in central Helsinki , 2003 .
[17] Stanislaw Osowski,et al. Fast Second Order Learning Algorithm for Feedforward Multilayer Neural Networks and its Applications , 1996, Neural Networks.
[18] Subhash C. Bagui,et al. Combining Pattern Classifiers: Methods and Algorithms , 2005, Technometrics.
[19] J. Hooyberghs,et al. A neural network forecast for daily average PM10 concentrations in Belgium , 2005 .
[20] Kurt Hornik,et al. The support vector machine under test , 2003, Neurocomputing.
[21] Kurt Hornik,et al. Multilayer feedforward networks are universal approximators , 1989, Neural Networks.
[22] Stéphane Mallat,et al. A Theory for Multiresolution Signal Decomposition: The Wavelet Representation , 1989, IEEE Trans. Pattern Anal. Mach. Intell..
[23] Bernhard Schölkopf,et al. Learning with kernels , 2001 .
[24] Mikko Kolehmainen,et al. Evolving the neural network model for forecasting air pollution time series , 2004, Eng. Appl. Artif. Intell..
[25] Georgios Grivas,et al. Artificial neural network models for prediction of PM10 hourly concentrations, in the Greater Area of Athens, Greece , 2006 .
[26] Gabriel Ibarra-Berastegi,et al. Regression and multilayer perceptron-based models to forecast hourly O3 and NO2 levels in the Bilbao area , 2006, Environ. Model. Softw..
[27] Vladimir Vapnik,et al. Statistical learning theory , 1998 .
[28] Kamaruzzaman Sopian,et al. Relationships between airborne particulate matter and meteorological variables using non-decimated wavelet transform , 2008 .
[29] Jason Weston,et al. Gene Selection for Cancer Classification using Support Vector Machines , 2002, Machine Learning.
[30] Jorge Reyes,et al. Prediction of maximum of 24-h average of PM10 concentrations 30 h in advance in Santiago, Chile , 2002 .
[31] Li-Yen Shue,et al. Data mining to aid policy making in air pollution management , 2004, Expert Syst. Appl..
[32] Jorge Reyes,et al. An integrated neural network model for PM10 forecasting , 2006 .
[33] W. Briggs. Statistical Methods in the Atmospheric Sciences , 2007 .