The Neural Network Assisted Land Use Regression

Land Use Regression (LUR) is one of the air quality assessment modelling techniques. Its advantages lie mainly in a much simpler mathematical apparatus, quicker and calculations, possibility to incorporate more factors affecting pollutant concentration than standard dispersion models. The goal study was perform LUR model Polish-Czech-Slovakian Tritia region, test two sets pollution data input factors, i.e., based on emission results, regression via neural networks compare it with linear regression. Both datasets, provided similar results case when used, R2 models 0.639 0.652. Neural network significantly higher models, their 0.937 0.938 for respectively.