Energy conservation and indoor environment concerns have motivated extensive research
on various aspects of control of Heating, Ventilating and Air-Conditioning (HVAC) and …

Predicting the load in a building is essential for the optimal control of heating, ventilating and
air-conditioning (HVAC) systems that use Ice Thermal Energy Storage (ITES) technology …

This study presents four modeling techniques for the prediction of hourly cooling load in the
building. In addition to the traditional back propagation neural network (BPNN), the radial …

A combination of JMP, PSO‐BP neural network, and Markov chain which aims at the low
correlation between input and output data and the error of prediction model in the PSO‐BP …

The electric power load during the summer peak time is strongly affected by cooling load,
which decreases the preparation ratio of electricity and brings about the failure in the supply …

The central air conditioning system provides city dwellers with an efficient and comfortable
environment. Meanwhile, coinciding with their use, the building electricity load is increased …

In this paper, support vector machine (SVM) is used to predict hourly building cooling load.
The hourly building cooling load prediction model based on SVM has been established, and …

Background: Energy conservation has always been a major issue in our country, and the air
conditioning energy consumption of buildings accounts for the majority of the energy …

Due to having the characters of non-linear and non-stationary, it is difficult to accurately
predict the air conditioning cooling load. In order to predict the load more accurately, this …

Since cooling and heating loads are regarded as significant parameters to examine the
energy performance of buildings, the need to predict and analyze them for the residential …