Evaluation of waste recycling of fruits based on Support Vector Machine (SVM)

Abstract

Abstract The purpose of this research is to investigate the effect of innovation management on recycling products and to use a new method based on artificial intelligence and a machine learning for innovative product recycled management. To this end, 170 employees of fruit and berry fields were selected among the municipality of Tehran in 2015 by proportional sampling method. A researcher-made questionnaire was used to measure the attitude towards waste recycling and recycling behavior. To calculate the correlation assumptions from SPSS software, the results of the first and second group questionnaires are compared with SPSS software. To analyze the data and the results of the questionnaire in each step, based on the support machine, the Matlab software is used. The results of the research showed that: (1) a new method based on artificial intelligence and machine learning can be used for innovative product recycling. (2) Innovation management affects the recycling of products. (3) There is a significant relationship between innovation management indicators and product recycling plans. (4) Investigating the Support Vector Machine (SVM) in measuring the standardized researcher-made questionnaire on waste recycling and recycling behavior.