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Feedforward neural network and adaptive network-based fuzzy inference system in study of power lines

M. Piradl, A. Jafarian


At present, the electric energy consumption is increasing much more rapidly and has a deleterious effect on the health and immune systems of human being. That is to say, the greater electromagnetic intensity creates negative conditions relatively easily, that might become problematic and have unpleasant consequences. Since electric fields have been a vital part of our daily life, everyone is exposed to both electric and magnetic fields (EMFs) which are emitted by electricity power lines, some electronic equipment and other sources. The invisible lines of power that surrounded any electrical device and the strength of these currents depend on the intensity of the outside voltage. Exposures to higher levels are might be harmful. The present study evaluates the negative influence of electric power systems in terms of the pylon height and the size of the land. The extent of the negative effects of electrical and magnetic fields around the power lines will be approximated using the fuzzy neural networks of the second kind which will be discussed in details in next section. All data has been kindly provided from the ministry of electricity of Urmia.Since it has already been proved that the fuzzy neural networks of the second kind have a higher accuracy in estimating the linear equations, the present study will utilize this type of fuzzy neural networks.


Electromagnetic fields, Power lines, Feed forward neural network, Adaptive neuro - Fuzzy inference system (ANFIS).

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