Hybrid ARIMA and Neural Network Modelling Applied to Telecommunications in Urban Environments in the Amazon Region

This study explores the use of a hybrid Autoregressive Integrated Moving Average (ARIMA) and Neural Network modelling for estimates of the electric field along vertical paths (buildings) close to Digital Television (DTV) transmitters. The work was carried out in Belem city, one of the most urbanized cities in the Brazilian Amazon and includes a case study of the application of this modelling within the subscenarios found in Belem. Its results were compared with the ITU recommendations P. 1546-5 and proved to be better in every subscenario analysed. In the worst case, the estimate of the model was approximately 65% better than that of the ITU. We also compared this modelling with a classic modelling technique: the Least Squares (LS) method. In most situations, the hybrid model achieved better results than the LS.

[1]  M. Ibrani,et al.  Comparative analysis of personal exposure levels induced by long-term evolution 1800 Re-farming and other RF sources in an urban environment , 2018 .

[3]  Ratnadip Adhikari,et al.  Time Series Forecasting Using Hybrid ARIMA and ANN Models Based on DWT Decomposition , 2015 .

[4]  D. Carpenter,et al.  Thermal and non-thermal health effects of low intensity non-ionizing radiation: An international perspective. , 2018, Environmental pollution.

[5]  Guoqiang Peter Zhang,et al.  Time series forecasting using a hybrid ARIMA and neural network model , 2003, Neurocomputing.

[6]  J. Bernhardt,et al.  Non-ionizing radiation safety: radiofrequency radiation, electric and magnetic fields , 1992, Physics in medicine and biology.

[7]  J. Lebbink,et al.  Semi-quantitative proteomics of mammalian cells upon short-term exposure to non-ionizing electromagnetic fields , 2017, PloS one.

[8]  Abhishek Singh,et al.  Hybrid ARIMA-ANN Modelling for Forecasting the Price of Robusta Coffee in India , 2017 .

[9]  K. Wang,et al.  Hybrid methodology for tuberculosis incidence time-series forecasting based on ARIMA and a NAR neural network , 2017, Epidemiology and Infection.

[10]  Jorge J. Moré,et al.  The Levenberg-Marquardt algo-rithm: Implementation and theory , 1977 .

[11]  Hossein Bonakdari,et al.  Integrated SARIMA with Neuro-Fuzzy Systems and Neural Networks for Monthly Inflow Prediction , 2017, Water Resources Management.

[12]  G. Box.  Box and Jenkins: Time Series Analysis, Forecasting and Control , 2013 .

[13]  Aleksandar Neskovic,et al.  Statistical analysis of electromagnetic radiation measurements in the vicinity of GSM/UMTS base station installed on buildings in Serbia. , 2016, Radiation protection dosimetry.

[14]  Çagdas Hakan Aladag,et al.  Forecasting nonlinear time series with a hybrid methodology , 2009, Appl. Math. Lett..