Cargando…
Predicting Site Energy Usage Intensity Using Machine Learning Models
Climate change is a shift in nature yet a devastating phenomenon, mainly caused by human activities, sometimes with the intent to generate usable energy required in humankind’s daily life. Addressing this alarming issue requires an urge for energy consumption evaluation. Predicting energy consumptio...
Autores principales: | Ngnamsie Njimbouom, Soualihou, Lee, Kwonwoo, Lee, Hyun, Kim, Jeongdong |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9823370/ https://www.ncbi.nlm.nih.gov/pubmed/36616680 http://dx.doi.org/10.3390/s23010082 |
Ejemplares similares
-
MMDCP: Multi-Modal Dental Caries Prediction for Decision Support System Using Deep Learning
por: Ngnamsie Njimbouom, Soualihou, et al.
Publicado: (2022) -
Optimal Feature Selection-Based Dental Caries Prediction Model Using Machine Learning for Decision Support System
por: Kang, In-Ae, et al.
Publicado: (2023) -
GCRNN: graph convolutional recurrent neural network for compound–protein interaction prediction
por: Elbasani, Ermal, et al.
Publicado: (2022) -
Machine Learning Model for the Prediction of Hemorrhage in Intensive Care Units
por: Kang, Sora, et al.
Publicado: (2022) -
Reinforcement Learning-Based BEMS Architecture for Energy Usage Optimization
por: Park, Sanguk, et al.
Publicado: (2020)