Estimation of waste mobile phones in the Philippines using neural networks - Galang, Mark Gino K. (College of Engineering, University of the Philippines Diliman, 2016)
Waste mobile phone is one of the subgroups of e-waste which is defined as discarded electronic products in Philippine context. This study estimated current and projected quantities of waste mobile phones in the country using feed forward neural network. The neural network architecture used had three (3) layers: input layer, hidden layer and output layer. Seven (7) input factors were fed to the network namely (1) population, (11) literacy rate, (iíi) mobile connections, (iv) mobile subscribers, (v) gross domestic product (GDP), (vi) GDP per capita and (vii) US dollar to peso exchange rate. The structure was designed with 5 hidden layers which consisted of; six (6) neurons for layer 1, five (5) neurons for layer 2, four (4) neurons for layer 3, three (3) neurons for layer 4 and two (2) neurons for layer 5. The neural network was designed to calculate first for the sales of mobile phones before estimating waste mobile phone generation. Visual Gene Developer 1.7 Software was used which showed an error of ±0.00001. Estimates and predicted values were found to be in good agreement with a calculated accuracy of 99%. This study can be used by policy makers as strategy, and as guideline and baseline data for establishing proper management system. Neural network performed better than the traditional linear extrapolation method for forecasting of data.