Design an Artificial Neural Network by MLP Method; Analysis of the Relationship between Demographic Variables,Resilience, COVID-19 and Burnout

In addition to the effect that the COVID-19 pandemic has had on the physical and mental health of individuals, ithas also led to a change in the mental and emotional state of many employees. Especially among businesses andprivate companies, which faced many restrictions due to the special conditions of the pandemic. Therefore, thepresent study aimed to design an artificial neural network with MLP technique to analyze the relationshipbetween demographic variables, resilience, COVID-19 and burnout in start-ups in Iran. The research methodwas quantitative. Managers and employees of start-ups formed the statistical population of the study, based onthe statistical sample size of the unlimited community, 384 of them were tested. For data gathering, standardquestionnaires include of MBI-GS and BRCS and researcher-made questionnaire of stress caused by COVID-19were used. The validity of the questionnaires was confirmed by a panel of experts and their reliability was confirmedby Cronbach’s alpha coefficient. The number of neurons in the input layer was equal to 10, the number of neurons inthe 1st hidden layer was equal to 7, the number of neurons in the output layer was equal to 1, and the number ofepochs was equal to 500. 70% of the data were used for training and 30% for testing. In the designed artificial neuralnetwork, all experiment data except one were correctly predicted and the obtained MAE error was less than 0.012%.Finally, he precision and correction of the presented model was confirmed by the obtained results.