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The present study analyses the electric field radiating from the GSM/UMTS base stations located in central Malatya, a densely populated urban area in Turkey. The authors have conducted both instant and continuous measurements of high-frequency electromagnetic fields throughout their research by using non-ionising radiation-monitoring networks. Over 15,000 instant and 13,000,000 continuous measurements were taken throughout the process. The authors have found that the normal electric field radiation can increase ∼25% during daytime, depending on mobile communication traffic. The authors' research work has also demonstrated the fact that the electric field intensity values can be modelled for each hour, day or week with the results obtained from continuous measurements. The authors have developed an estimation model based on these values, including mobile communication traffic (Erlang) values obtained from mobile phone base stations and the temperature and humidity values in the environment. The authors believe that their proposed artificial neural network model and multivariable least-squares regression analysis will help predict the electric field intensity in an environment in advance.

This paper presents the use of the generalized classical method (GCM) for solving linear and nonlinear differential equations. This method is based on the differential transformation (DT) technique. In the GCM, the solution of the nonlinear transient regimes in the physical processes can be written as a functional series with unknown coefficients. The series can be chosen to satisfy the initial and boundary conditions which represent the properties of the physical process. The unknown coefficients of the series are determined from the differential transformation of the nonlinear differential equation of the system. Therefore, the approximate solution of the nonlinear differential equation can be obtained as a closed-form series.The validity and efficiency of the GCM is shown using some transient regime problems in the electromechanics processes. The numerical results obtained by the present method are compared with the analytical solutions of the equations. It is shown that the results are found to be in good agreement with each other.

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