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Application Of Artificial Neural Networks To Assess Student Happiness, Gokhan Egilmez, Nadiye O. Erdil, Omid Mohammadi Arani, Mana Vahid

Mechanical and Industrial Engineering Faculty Publications

The purpose of this study is to develop an analytical assessment approach to identify the main factors that affect graduate students' happiness level. The two methods, multiple linear regression (MLR) and artificial neural networks (ANN), were employed for analytical modelling. A sample of 118 students at a small non-profit private university constituted the survey pool. Various factors including education, school facilities, health, social activities, and family were taken into consideration as a result of literature review in happiness assessment. A total of 32 inputs and one output variables were identified during survey design phase. The following survey conduction, data collection, …