Modelling of forest fires time evolution in the USA on the basis of long term variations and dynamics of the temperature of the solar wind protons

Abstract

The work examines the potential causative link between the flow of protons, i.e. temperature of the particles that are coming from the sun and forest fires in the USA. For determination of the degree of randomness for time series of input (temperature of protons) and output parameters (number of forest fires), the R/S analysis is conducted. The analysis of fractal dimension provides us an opportunity to compare self-similar processes in the influx of protons and the time series of forest fires flashes. Therefore we developed and conducted the sensitivity analysis of model based on hybrid neural networks ANFIS. As the calculations showed, only 16% of the real forest flashes cannot be predicted by the model.