@inproceedings{6e5a68bec6dd40bb8fa3c766db3e584d,
title = "An artificial neural network model for predicting building heating and cooling loads",
abstract = "In this work, an artificial neural network is designed for predicting the heating and cooling loads for buildings. The paper develops two neural models that make use of a dataset with 8 input attributes with the output as a numeric value of the heating and cooling loads of the buildings. The predictive abilities of the neural nets are compared with linear regression under conventional validation, 5-fold validation and 10-fold validation. Obtained results show that both neural models obtain encouraging results and can be dependably deployed in building loads determination.",
keywords = "Artificial neural networks, Cooling loads, Heating loads, Linear regression",
author = "Nwulu, {Nnamdi I.}",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 International Artificial Intelligence and Data Processing Symposium, IDAP 2017 ; Conference date: 16-09-2017 Through 17-09-2017",
year = "2017",
month = oct,
day = "30",
doi = "10.1109/IDAP.2017.8090314",
language = "English",
series = "IDAP 2017 - International Artificial Intelligence and Data Processing Symposium",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "IDAP 2017 - International Artificial Intelligence and Data Processing Symposium",
address = "United States",
}