Open AccessHybrid Modeling of Central Air-Conditioning Cold Source System Energy Consumption with K-means Cluster Algorithm
Author(s) -
Zhihao Zhou
Publication year - 2019
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/295/5/052035
Subject(s) - artificial neural network , gray (unit) , energy consumption , computer science , air conditioning , central air conditioning , cluster (spacecraft) , algorithm , artificial intelligence , engineering , medicine , mechanical engineering , electrical engineering , radiology , programming language
Gray box model and artificial neural network (ANN) model of central air-conditioning cold source system have been established with simulation data to predict system operation energy consumption and compare the prediction accuracy difference of models under variable training data. A hybrid model is proposed to combine gray box model and ANN model based on K-means cluster algorithm. The results show that ANN model has higher prediction accuracy than gray box model when the membership of model input variables to trained input data is greater than 0.4. Otherwise, the gray box model has higher energy consumption prediction accuracy. Compared with gray box model and ANN model, prediction accuracy of hybrid model increases 27.7% and 33.85% on average under different training data.