Prediction of Magnetic Pollution with Artificial Neural Network in Living Areas

Abstract

The high voltage transmission and distribution lines are source of the extremely low frequencies (ELF) radiation. The increasing use of transmission of electrical energy is causing concerns regarding the risks of human exposure to ELF from the lines. In recent years studies investigating the interaction of ELF magnetic fields with human body have become important. Epidemiological studies report that magnetic fields emitted from power lines increase the incidence of leukemia in the children of people living near power lines. In the municipality of Nilufer with a population of 600,000 in Bursa province, which is one of the largest cities in Turkey, high voltage lines pass over residential areas or very close to houses and schools. Studies are being carried out to reduce electromagnetic pollution in this region. Within the scope of this study, magnetic field measurement values arising from high voltage lines were taken between 2014 and 2019. In order to make sense of these values, first of all analyzes were made by mapping. After the analysis, the data set was created by labeling. Using the data set created, magnetic measurement values were trained based on parameters in dataset. After the training, the predictions and actual results were compared by testing with the data not used during the training. In addition, by making 3D drawings according to the latitude and longitude of the region, places where electromagnetic pollution may be high were found and measures were taken for these places.