Forecasting concentrations of air pollutants by logarithm support vector regression with immune algorithms

DOI10.1016/J.AMC.2010.11.055zbMath1207.92048OpenAlexW2029613065MaRDI QIDQ628876

Shun-Ling Yang, Kuo-Ping Lin, Ping-Feng Pai

Publication date: 8 March 2011

Published in: Applied Mathematics and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.amc.2010.11.055

zbMATH Keywords

parameter selectionsupport vector regressiondata preprocessingimmune algorithmsconcentrations of air pollutants

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to biology and medical sciences; meta analysis (62P10) Ecology (92D40)

Related Items (2)

Reinforcement radial basis function neural networks with an adaptive annealing learning algorithm ⋮ A deep multitask learning approach for air quality prediction

Cites Work

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• An immune algorithm approach to hybrid flow shops scheduling with sequence-dependent setup times
• Improved immune algorithm for global numerical optimization and job-shop scheduling problems
• Neural network forecasting for seasonal and trend time series
• The impact of preprocessing on data mining: an evaluation of classifier sensitivity in direct marketing
• Application of SVM and ANN for image retrieval
• Learning representations by back-propagating errors

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