Comparison of neural network models with ARIMA and regression models for prediction of Houston's daily maximum ozone concentrations.
Victor R. PrybutokJunsub YiDavid MitchellPublished in: Eur. J. Oper. Res. (2000)
Keyphrases
- regression model
- neural network model
- prediction model
- artificial neural networks
- linear regression model
- target variable
- neural network
- input variables
- exponential smoothing
- multiple linear regression
- survival analysis
- air pollution
- regression methods
- multi layer perceptron
- regression analysis
- solar radiation
- support vector regression
- bp neural network
- radial basis function network
- generalized linear models
- neural models
- forecasting accuracy
- model selection
- explanatory variables
- gaussian process
- rbf neural network
- generalized linear
- short term
- autoregressive integrated moving average
- arima model
- moving average
- hybrid model
- multilayer perceptron
- software effort
- bayesian models
- software reliability
- regression trees
- predictive model
- gaussian processes
- multivariate regression
- feature selection