Using artificial intelligence (AI) models, cost effective electricity meter, and easily accessible
weather data, this paper discusses a methodology for improved prediction of hourly …

This study aimed to develop a control algorithm that can operate a variable refrigerant flow
(VRF) cooling system with optimal set-points for the system variables. An artificial neural …

Energy consumption prediction for building energy management systems (BEMS) is one of
the key factors in the success of energy saving measures in modern building operation …

The study aims to effectively reduce building energy consumption, improve the utilization
efficiency of building resources, reduce the emission of pollutants and greenhouse gases …

Energy efficiency in modern homes has recently become a significant concern due to the
emergence of smart-home infrastructure. Numerous public structures, such as homes …

Building energy consumption prediction provides the possibility for regulating running
condition of equipments in advance. Then the equipments will keep good movement and …

This study investigates the application of machine learning techniques to predict energy
consumption in buildings. Five machine learning models (linear regression, decision trees …

In this study, data-mining techniques comprising three forecasting algorithms for accurate
and precise cooling load requirement prediction in the building environment, with the …

Although energy sources on the environment are limited, in all parts of life, energy
requirement increases rapidly which depends on the increasing technology and population …

It is of great significance to achieve the prediction of building energy consumption. However,
machine learning, as a promising technique for many practical applications, was rarely …