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

Q2 Environmental Science

Cogent Environmental Science Pub Date : 2020-01-01 DOI:10.1080/23311843.2020.1712146

Javad Farjami, S. Dehyouri, M. Mohamadi

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引用次数: 2

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.

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基于支持向量机的水果废弃物回收利用评价

摘要本研究的目的是研究创新管理对回收产品的影响，并使用基于人工智能和机器学习的新方法进行创新产品回收管理。为此，2015年，通过比例抽样法在德黑兰市选出了170名水果和浆果领域的员工。研究人员制作了一份问卷来衡量人们对废物回收的态度和回收行为。为了计算SPSS软件的相关性假设，将第一组和第二组问卷的结果与SPSS软件进行比较。为了分析每一步的数据和问卷调查结果，在支持机的基础上，使用了Matlab软件。研究结果表明：（1）一种基于人工智能和机器学习的新方法可以用于创新产品回收。（2）创新管理影响产品的回收利用。（3）创新管理指标与产品回收计划之间存在显著关系。（4）调查采用支持向量机（SVM）对标准化研究人员制作的垃圾回收利用行为问卷进行测量。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Cogent Environmental Science ENVIRONMENTAL SCIENCES-

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审稿时长

13 weeks