Classic linear assignment method is a multi-criteria decision-making approach in which criteria are weighted and each rank is assigned to a choice. In this study, to abandon the requirement of calculating the weight of criteria and use decision attributes prioritizing and also to be able to assign a rank to more than one choice, a multi-objective linear programming (MOLP) method is suggested. The objective function of MOLP is defined for each attribute and MOLP is solved based on absolute priority and comprehensive criteria methods. For solving the linear programming problems we apply a recurrent neural network (RNN). Indeed, the Lyapunov stability of the model is proved. Results of comparing the proposed method with TOPSIS, VICOR, and MOORA methods which are the most common multi-criteria decision schemes show that the proposed approach is more compatible with these methods.
Purpose: The present study aimed to examine the effect of physical activity on the quality of life and mental health of Ferdowsi University students whose field of study was not physical education during the COVID-19 Pandemic. Method: The method of study was descriptive and correlational. The statistical population of this present study consisted of all male and female students of Ferdowsi University whose field of study was not physical education and they had chosen physical education 1 and Sports 1. Data were collected from 375 Ferdowsi University students whose field of study was not physical education and they were selected randomly. Data collection was done through Physical Activity Questionnaire by Wickramarachchi et al. (2021), Mental Health Questionnaire by Proto. & Quintana-Domeque (2021), and Quality of Life Questionnaire by Epifanio et al. (2021). The validity and reliability of the questionnaires were also confirmed and Structural Equation Modeling (SEM) was used to analyze the data.Findings: The results showed a direct and statistically significant effect of physical activities on the quality of life, which was obtained at 0.958.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.