Author

Maya Arida

North Carolina A&T State University, United States

3 articles in our journals

Articles where this person is an author, newest first. People are matched by their name as printed (no ORCID iD is recorded for them), not by name alone; search the name as text to find namesakes too.

Research ArticleOpen accessChilled Water VAV System Optimization and Modeling Using Artificial Neural NetworksRand Talib, Nabil Nassif, Maya Arida, Taher Abu-LebdehIn 2016, It was estimated that about 40% of total U.S. energy consumption was consumed by the residential and commercial sectors. According to EIA, in 2009, the energy consumption in U.S. homes was 48% which was down from 58% in 1993 (Residential Energy Consumption Survey (RECS). The development of building energy savings methods and models becomes apparently more necessary for … …Energy Research Journal, Vol. 9, Issue 1 · 6 Feb 2019 · 6,449 accessesView PDF Cite

Research ArticleOpen accessChilled Water VAV System Optimization and Modeling Using Artificial Neural NetworksRand Talib, Nabil Nassif, Maya Arida, Taher Abu-Lebdehin 2016, It was estimated that about 40% of total U.S. energy consumption was consumed by the residential and commercial sectors. According to EIA, in 2009, the energy consumption in U.S. homes was 48% which was down from 58% in 1993 Residential Energy Consumption Survey (RECS). The development of building energy savings methods and models becomes apparently more necessary for … …American Journal of Engineering and Applied Sciences, Vol. 11, Issue 4 · 23 Oct 2018 · 7,465 accessesView PDF Cite

Research ArticleOpen accessBuilding Energy Modeling Using Artificial Neural NetworksMaya Arida, Nabil Nassif, Rand Talib, Taher Abu-LebdehAccurate modeling of total building energy is now vital to reduce energy consumption. This is especially true for buildings since they are considered as the largest energy consumer in the United States. This paper investigates modeling methods for building energy-systems using non-linear auto-regression artificial neural networks. The proposed model can forecast the whole building energy consumptions given the four input … …Energy Research Journal, Vol. 7, Issue 2 · 6 Jun 2017 · 7,125 accessesView PDF Cite