@inproceedings{deecc6068ffd4cadb5f5f884e11f3fff,
title = "Assessing the possible potential in the global energy consumption: Integrated artificial neural network and data envelopment analysis",
abstract = "Energy is fundamental to attaining various objectives globally. Its conservation and optimal use will help achieve the numerous objectives. Energy use has been well analyzed and assessed for different purposes using Artificial Neural Network (ANN) and Data Envelopment Analysis (DEA). This study has looked at the various benefits that can be acquired using these methods leading to the significance of developing an integrated model. To determine how much energy could be conserved globally, the integrated model was developed. The model applied to the global energy consumption from 1995 to 2009 discovered a possible saving of 1.62% that could have been conserved.",
keywords = "Artificial Neural Network, Data Envelopment Analysis, Global energy consumption, Integrated model",
author = "Olanrewaju, {O. A.} and C. Mbohwa",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2017 ; Conference date: 10-12-2017 Through 13-12-2017",
year = "2017",
month = jul,
day = "2",
doi = "10.1109/IEEM.2017.8290152",
language = "English",
series = "IEEE International Conference on Industrial Engineering and Engineering Management",
publisher = "IEEE Computer Society",
pages = "1546--1550",
booktitle = "2017 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2017",
address = "United States",
}