Art

J-GLOBAL ID：202402266633908677   Reference number：24A0342746

Solid Waste Generation and Disposal Using Machine Learning Approaches: A Survey of Solutions and Challenges

機械学習アプローチを用いた固形廃棄物の発生と処分:解決策と挑戦の調査【JST・京大機械翻訳】

Author (7)： Namoun Abdallah (Faculty of Computer and Information Systems, Islamic University of Madinah, Madinah 42351, Saudi Arabia) ,  Tufail Ali (School of Digital Science, Universiti Brunei Darussalam, Tungku Link, Gadong BE1410, Brunei) ,  Khan Muhammad Yasar (Malaysian Institute of Information Technology (MIIT), University of Kuala Lumpur, Kuala Lumpur 50250, Malaysia) ,  Alrehaili Ahmed (Faculty of Computer and Information Systems, Islamic University of Madinah, Madinah 42351, Saudi Arabia) ,  Alrehaili Ahmed (Department of Informatics, University of Sussex, Brighton BN1 9RH, UK) ,  Syed Toqeer Ali (Faculty of Computer and Information Systems, Islamic University of Madinah, Madinah 42351, Saudi Arabia) ,  BenRhouma Oussama (Faculty of Computer and Information Systems, Islamic University of Madinah, Madinah 42351, Saudi Arabia)
Material： Sustainability (Web)
Volume： 14  Issue： 20  Page： 13578  Publication year： 2022 
JST Material Number： U7281A  ISSN： 2071-1050  Document type： Article
Article type： 文献レビュー  Country of issue： Switzerland (CHE)  Language： ENGLISH (EN)

Abstract/Point： We present a survey of machine...

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Thesaurus term： reliability(property) ,  database ,  neural network(biomodel) ,  *waste ,  city ,  *solid waste ,  long term forecast ,  computation model ,  waste management(radioactive) ,  *machine learning ,  analytical model ,  prediction model
Semi thesaurus term： 独立変数 ,  回帰木 ,  廃棄物発生 , 【Automatic Indexing@JST】

Author keywords (7)： smart waste management ,  solid waste generation ,  waste disposal ,  artificial intelligence ,  machine learning ,  deep learning ,  smart cities

JST classification (2)： Waste treatment in general  (SC05010S) ,  Refuse treatment  (SC05030O)

Reference (91)：

• United Nations, Department of Economic and Social Affairs. Available online: https://www.un.org/development/desa/en/news/population/2018-revision-of-world-urbanization-prospects.html (accessed on 17 August 2022).
• Kaza, S.; Yao, L.; Bhada-Tata, P.; van Woerden, F. What a Waste 2.0: A Global Snapshot of Solid Waste Management to 2050; World Bank Publications: Herndon, VA, USA, 2018.
• Kumar, S.; Yadav, D.; Gupta, H.; Verma, O.P.; Ansari, I.A.; Ahn, C.W. A Novel YOLOv3 Algorithm-Based Deep Learning Approach for Waste Segregation: Towards Smart Waste Management. Electronics 2021, 10, 14.
• Mahajan, P.S.A.; Kokane, A.; Shewale, A.; Shinde, M.; Ingale, S. Smart Waste Management System using IoT. Int. J. Adv. Eng. Res. Sci. 2017, 4, 93-95.
• Alqahtani, F.; Al-Makhadmeh, Z.; Tolba, A.; Said, W. Internet of things-based urban waste management system for smart cities using a Cuckoo Search Algorithm. Cluster Comput. 2020, 23, 1769-1780.

Terms in the title (4)： 機械学習 ,  固形廃棄物 ,  解決策 ,  調査