Comparative study of predicting hospital solid waste generation using multiple linear regression and artificial intelligence

被引：0
|
作者：
Somayeh Golbaz
Ramin Nabizadeh
Haniye Sadat Sajadi
机构：
[1] Tehran University of Medical Sciences,Department of Environmental Health Engineering, School of Public Health
[2] Tehran University of Medical Sciences,Health Services Management, National Institute for Health Research
来源：
Journal of Environmental Health Science and Engineering | 2019年 / 17卷
关键词：
Multiple linear regression; Machine learning method; Hospital; Solid waste;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
引用
收藏
页码：41 / 51
页数：10
相关论文
共 50 条
  • [41] Modeling the energy content of municipal solid waste using multiple regression analysis
    Liu, JI
    Paode, RD
    Holsen, TM
    JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION, 1996, 46 (07): : 650 - 656
  • [42] Modeling the energy content of municipal solid waste using multiple regression analysis
    Environmental Planning Division, Kaohsiung Dept. of Environ. Protect., Kaohsiung, Taiwan
    不详
    不详
    不详
    J. AIR WASTE MANAGE. ASSOC., 7 (650-656):
  • [43] Forecasting of wind speed using multiple linear regression and artificial neural networks
    Barhmi, Soukaina
    Elfatni, Omkaltoume
    Belhaj, Ismail
    ENERGY SYSTEMS-OPTIMIZATION MODELING SIMULATION AND ECONOMIC ASPECTS, 2020, 11 (04): : 935 - 946
  • [44] Forecasting of wind speed using multiple linear regression and artificial neural networks
    Soukaina Barhmi
    Omkaltoume Elfatni
    Ismail Belhaj
    Energy Systems, 2020, 11 : 935 - 946
  • [45] Using Artificial Neural Network and Multiple Linear Regression for Predicting the Chlorophyll Concentration Index of Saint John's Wort Leaves
    Odabas, Mehmet Serhat
    Kayhan, Gokhan
    Ergun, Erhan
    Senyer, Nurettin
    COMMUNICATIONS IN SOIL SCIENCE AND PLANT ANALYSIS, 2016, 47 (02) : 237 - 245
  • [46] Assessment of Algorithm Performance on Predicting Total Dissolved Solids Using Artificial Neural Network and Multiple Linear Regression for the Groundwater Data
    Farooq, Muhammad Umar
    Zafar, Abdul Mannan
    Raheem, Warda
    Jalees, Muhammad Irfan
    Hassan, Ashraf Aly
    WATER, 2022, 14 (13)
  • [47] Predicting saturated and near-saturated hydraulic conductivity using artificial neural networks and multiple linear regression in calcareous soils
    Mozaffari, Hasan
    Moosavi, Ali Akbar
    Nematollahi, Mohammad Amin
    PLOS ONE, 2024, 19 (01):
  • [48] MODELING THE QUANTITY OF MUNICIPAL SOLID WASTE IN ISTANBUL BY USING ARTIFICIAL INTELLIGENCE AND STATISTICAL TECHNIQUES
    Goren, Sami
    Anil, Ismail
    Camci, Fatih
    Sengul, Ayse B.
    Mehan, Hatice N. Aras
    SIGMA JOURNAL OF ENGINEERING AND NATURAL SCIENCES-SIGMA MUHENDISLIK VE FEN BILIMLERI DERGISI, 2011, 3 (01): : 165 - 175
  • [49] Sales forecasting for a Turkish paint producer: Artificial intelligence based methods versus Multiple Linear Regression
    Ustundag, Alp
    Cevikcan, Emre
    Kilinc, Mehmet Serdar
    COMPUTATIONAL INTELLIGENCE IN DECISION AND CONTROL, 2008, 1 : 49 - 54
  • [50] Object Detection Based Management System of Solid Waste Using Artificial Intelligence Techniques
    Chowdhury, Tanvir Ahmed
    Sinthiya, Nusrat Jahan
    Shanta, S. M. Sajid Hasan
    Hasan, Md. Tasbiul
    Habib, Mubassir
    Rahman, Rashedur M.
    2022 IEEE 13TH ANNUAL UBIQUITOUS COMPUTING, ELECTRONICS & MOBILE COMMUNICATION CONFERENCE (UEMCON), 2022, : 19 - 23
12345