Prediction of hourly ozone concentrations with multiple regression and multilayer perceptron models

Multilayer perceptron and regression modelling to forecast hourly nitrogen dioxide concentrations

This paper presents the application of feed-forward multilayer perceptron networks and multiple regression models, to forecast hourly nitrogen dioxide levels 24 hours in advance. Input data are traffic and meteorological variables, and nitrogen dioxide hourly levels. The introduction of four periodic components (sine and cosine terms for the daily and weekly cycles), and nitrogen oxide hourly l...

Prediction of daily evaporation using hybrid support vector regression-firefly optimization algorithm and multilayer perceptron

Prediction of daily evaporation is a valuable and determinant tool in sustainable agriculture and hydrological issues, especially in the design and management of water resources systems. Therefore, in this study, the ability of artificial intelligence models of multi-layer perceptron (MLP), support vector regression (SVR), and the hybrid model of support vector regression-firefly optimization a...

Predicting tropospheric ozone concentrations in different temporal scales by using multilayer perceptron models

Efficient estimation of multidimensional regression model with multilayer perceptron

Abstract. This work concerns estimation of multidimensional nonlinear regression models using multilayer perceptron (MLP). The main problem with such model is that we have to know the covariance matrix of the noise to get optimal estimator. however we show that, if we choose as cost function the logarithm of the determinant of the empirical error covariance matrix, we get an asymptotically opti...

Comparison of neural network models with ARIMA and regression models for prediction of Houston's daily maximum ozone concentrations

In an e€ort to forecast daily maximum ozone concentrations, many researchers have developed daily ozone forecasting models. However, this continuing worldwide environmental problem suggests the need for more accurate models. Development of these models is dicult because the meteorological variables and photochemical reactions involved in ozone formation are complex. In this study, a neural net...