Jelena Srebric
Biographic Data
| ID | 8209037 |
|---|---|
| NAME | Jelena Srebric |
| GIVEN NAMES | Jelena |
| FAMILY NAME | Srebric |
| SIGNATURE | SREBRIC J |
| AFFILIATIONS | University of Maryland, College Park |
| ORCID | 0000-0001-6825-5091 |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 4 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2018 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Investigating the impact of data normalization methods on predicting electricity consumption in a building using different artificial neural network models
The novel analysis strategy developed to understand data normalization method. • The significant influence of data normalization on the predictive capabilities of various ANN models • More effective combinations of ANN models with specific data normalization strategies • Evaluating the correlation between each data normalization method on the energy consumption The study investigates the impact of data normalization on the prediction of electrici…
Impact of correlation of plug load data, occupancy rates and local weather conditions on electricity consumption in a building using four back-propagation neural network models
Predictions of electricity consumption in a campus building using occupant rates and weather elements with sensitivity analysis
An extensive comparison of modified zero-equation, standard k-ε, and LES models in predicting urban airflow
No prominent works on this page.
An extensive comparison of modified zero-equation, standard k-ε, and LES models in predicting urban airflow
Impact of correlation of plug load data, occupancy rates and local weather conditions on electricity consumption in a building using four back-propagation neural network models
Predictions of electricity consumption in a campus building using occupant rates and weather elements with sensitivity analysis
Investigating the impact of data normalization methods on predicting electricity consumption in a building using different artificial neural network models
The novel analysis strategy developed to understand data normalization method. • The significant influence of data normalization on the predictive capabilities of various ANN models • More effective combinations of ANN models with specific data normalization strategies • Evaluating the correlation between each data normalization method on the energy consumption The study investigates the impact of data normalization on the prediction of electrici…
Building Energy and Comfort Optimization (4 works) · Engineering (4 works) · Artificial Intelligence (3 works) · Artificial neural network (3 works) · Computer Science (3 works) · Electricity (3 works) · Energy Load and Power Forecasting (3 works) · Environmental Science (3 works) · Simulation (3 works) · Civil engineering (2 works)