Total Solar Irradiance and Stroke Mortality by Neural Networks Modelling

Abstract

The purpose of this study was to examine the potential effect of solar energy on vascular stroke mortality in a Greek region by using neural networks analysis. The time period studied was from 1985 to 1989. We employed the Active Cavity Radiometer Irradiance Monitoring (ACRIM) data as the main representatives of total solar irradiance (TSI) and correlated them with stroke deaths obtained from the Piraeus City Registry. The ACRIM data (parameters included TSI, TSI uncertainty, and EPOCH: time given by ACRIM) were correlated with stroke deaths using Principal Components Analysis (PCA), regressions, and, finally, neural networks. TSI was the most important parameter for the years 1985, 1986, 1987, and 1989, while EPOCH: time given by ACRIM was important for the year 1988. When considering the entire period 1985–1989, the key parameter emerged was EPOCH: time given by ACRIM. Neural networks are useful tools in exposomic investigation regarding solar energy and vascular strokes.

Keywords

• TSI
• machine learning
• neural networks
• strokes
• electromagnetic fields
• solar energy