用人工神经网络预测垃圾管理系统的人类家庭行为模型

Q3 Economics, Econometrics and Finance
Rohana Sham, N. A. Izni, Nor Asiah Mahmood, Nur Ilyana Ismarau Tajuddin
{"title":"用人工神经网络预测垃圾管理系统的人类家庭行为模型","authors":"Rohana Sham, N. A. Izni, Nor Asiah Mahmood, Nur Ilyana Ismarau Tajuddin","doi":"10.60016/majcafe.v31.08","DOIUrl":null,"url":null,"abstract":"Efficient management of household trash is essential to maintaining a sustainable society and a good environment. Low community engagement in environmental cleanup has led to dozens of unused refuse management apps. Today’s refuse management system lacks a secure identification protocol for identifying users, especially those who have signed up for the app. Predicting and understanding human household behavior is needed, and it remains a complex challenge. Therefore, this study aims to predict human household behavior in the refuse management system using artificial neural networks (ANN). The work involved in developing the prediction model included data collection, data pre-processing, neural network model development, and performance validation. There are 505 participants, urban residents in Kuala Lumpur obtained for this study. ANN with one hidden layer is developed in MATLAB. The results show that the accuracy of the developed model is 83%. It indicates that ANN performed well in predicting household behavior in the refuse management system.","PeriodicalId":39091,"journal":{"name":"Malaysian Journal of Consumer and Family Economics","volume":"66 11","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Prediction Model of Human Household Behavior of the Refuse Management System with Artificial Neural Network\",\"authors\":\"Rohana Sham, N. A. Izni, Nor Asiah Mahmood, Nur Ilyana Ismarau Tajuddin\",\"doi\":\"10.60016/majcafe.v31.08\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Efficient management of household trash is essential to maintaining a sustainable society and a good environment. Low community engagement in environmental cleanup has led to dozens of unused refuse management apps. Today’s refuse management system lacks a secure identification protocol for identifying users, especially those who have signed up for the app. Predicting and understanding human household behavior is needed, and it remains a complex challenge. Therefore, this study aims to predict human household behavior in the refuse management system using artificial neural networks (ANN). The work involved in developing the prediction model included data collection, data pre-processing, neural network model development, and performance validation. There are 505 participants, urban residents in Kuala Lumpur obtained for this study. ANN with one hidden layer is developed in MATLAB. The results show that the accuracy of the developed model is 83%. It indicates that ANN performed well in predicting household behavior in the refuse management system.\",\"PeriodicalId\":39091,\"journal\":{\"name\":\"Malaysian Journal of Consumer and Family Economics\",\"volume\":\"66 11\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Malaysian Journal of Consumer and Family Economics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.60016/majcafe.v31.08\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Economics, Econometrics and Finance\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Malaysian Journal of Consumer and Family Economics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.60016/majcafe.v31.08","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Economics, Econometrics and Finance","Score":null,"Total":0}
引用次数: 0

摘要

有效管理生活垃圾对于维持可持续发展的社会和良好的环境至关重要。社区对环境清理的参与度较低,导致了数十个未使用的垃圾管理应用程序。目前的垃圾管理系统缺乏安全的身份识别协议来识别用户,尤其是那些注册了该应用程序的用户。预测和理解人类家庭行为是必要的,这仍然是一项复杂的挑战。因此,本研究旨在利用人工神经网络(ANN)预测垃圾管理系统中的人类家庭行为。开发预测模型所涉及的工作包括数据收集、数据预处理、神经网络模型开发和性能验证。参与本研究的有505名吉隆坡城市居民。在MATLAB中开发了一种单隐层神经网络。结果表明,所建立模型的准确率为83%。结果表明,人工神经网络在垃圾管理系统中具有较好的预测家庭行为的效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Prediction Model of Human Household Behavior of the Refuse Management System with Artificial Neural Network
Efficient management of household trash is essential to maintaining a sustainable society and a good environment. Low community engagement in environmental cleanup has led to dozens of unused refuse management apps. Today’s refuse management system lacks a secure identification protocol for identifying users, especially those who have signed up for the app. Predicting and understanding human household behavior is needed, and it remains a complex challenge. Therefore, this study aims to predict human household behavior in the refuse management system using artificial neural networks (ANN). The work involved in developing the prediction model included data collection, data pre-processing, neural network model development, and performance validation. There are 505 participants, urban residents in Kuala Lumpur obtained for this study. ANN with one hidden layer is developed in MATLAB. The results show that the accuracy of the developed model is 83%. It indicates that ANN performed well in predicting household behavior in the refuse management system.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Malaysian Journal of Consumer and Family Economics
Malaysian Journal of Consumer and Family Economics Economics, Econometrics and Finance-Economics, Econometrics and Finance (all)
CiteScore
1.10
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信