作者
Sagheer Abbas, Muhammad Adnan Khan, Luis Eduardo Falcon-Morales, Abdur Rehman, Yousaf Saeed, Mahdi Zareei, Asim Zeb, Ehab Mahmoud Mohamed
发表日期
2020/2/27
期刊
IEEE Access
卷号
8
页码范围
39982-39997
出版商
IEEE
简介
A smart city is a sustainable and effective metropolitan hub, that offers its residents high excellence of life through appropriate resource management. Energy management is among the most challenging problems in such metropolitan areas due to the difficulty and key role of energy systems. To optimize the benefit from the available megawatt-hours, it is important to predict the maximum electrical power output of a baseload power plant. This paper explores the method of a deep extreme learning machine to create a predictive model that can predict a combined cycle power plant's hourly full-load electrical output. An intelligent energy management solution can be achieved by properly monitoring and controlling these resources through the internet of things (IoT). The universe of artificial intelligence has produced many strides through deep learning algorithms and these methods were used for data analysis …
引用总数
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