An adaptive neuro-fuzzy inference system (ANFIS) approach to waste mobile phone estimation in the Philippines - Saludes, Roxanne Z.; Ballesteros, Florencio C. Jr. (Quezon City College of Engineering, University of the Philippines Diliman, 2018)
The Adaptive neuro-fuzzy inference system (ANFIS) is a soft computing model characterized by neural network adaptive capabilities and fuzzy logic qualitative approach. In this study, the model is used for estimating waste mobile phone generation in the Philippines. Input factors are classified and analyzed in SPSS and combined to get the best input combination for the ANFIS model. Historical data of input factors are fuzzified and evaluated using the neuro-fuzzy toolbox of MATLAB. Dataset is divided into three groups, 70%, 15% and 15%, for training, testing and checking of the new model. Mobile subscription, Population and GDP is the best 3-input combination determined by correlation analysis. Generated waste mobile phone is calculated using the lifespan data from survey and predicted sales of mobile phones. The ANFIS predicted values indicate that sales of mobile phones will reach 27.5 million units in 2108 to 32.7 million units in 2021. Moreover, estimated values show that 25.2 million units of waste mobile phones will be generated in 2018 and will reach 30.6 million units in 2021. The developed ANFIS model can be used as guideline in establishing comprehensive system of waste management in the Philippines
Thesis (Master of Science in Environmental Engineering)--University of the Philippines Diliman
Keywords: Electronic waste -- Philippines; Adaptive neuro-fuzzy inference system (ANFIS).