Mohamed Saad, Yingzhong Zhang, Jia Jia, Jinghai Tian
Decision tree-based approach to extrapolate life cycle inventory data of manufacturing processes
Journal of environmental management
paper explores methodologies enhance integration green supply chain circular economy within smart cities incorporating machine learning technology refine precision effectiveness prediction model gravitational algorithm introduced optimize parameter selection support vector machine model nationwide prediction model green supply chain economic development efficiency meticulously constructed leveraging public economic environmental demographic data comprehensive empirical analysis follows revealing noteworthy reduction mean squared error root mean squared error increasing iterations reaching minimum 0007 0103 respectivelyfigures lowest among considered machine learning models moreover mean absolute percentage error value remarkably low 00923 data illustrate gradual decline average prediction error standard deviation throughout model optimization process indicative model convergence heightened prediction accuracy results underscore significant potential machine learning technology optimizing supply chain circular economy management paper provides valuable insights decisionmakers researchers navigating landscape sustainable development