Predictions of Weekly Slope Movements Using Moving-Average and Neural Network Methods: A Case Study in Chamoli, India

2020 ◽  
pp. 67-81
Author(s):  
Praveen Kumar ◽  
Priyanka ◽  
Ankush Pathania ◽  
Shubham Agarwal ◽  
Naresh Mali ◽  
...  
Keyword(s):  
Neural Network ◽  
Moving Average ◽  
Slope Movements ◽  
Network Methods

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

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Ramz L. Fraiha Lopes ◽  
Simone G. C. Fraiha ◽  
Vinicius D. Lima ◽  
Herminio S. Gomes ◽  
Gervásio P. S. Cavalcante
Keyword(s):  
Neural Network ◽  
Moving Average ◽  
Urban Environments ◽  
Digital Television ◽  
Network Modelling ◽  
Worst Case ◽  
Autoregressive Integrated Moving Average ◽  
Neural Network Modelling ◽  
Better Than

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 Belém 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 Belém. 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.

Sign in / Sign up

Export Citation Format

Share Document