Learning to REDUCE: A Reduced Electricity Consumption Prediction Ensemble. | 2 | 0.39 | 2016 |
Influence-Driven Model For Time Series Prediction From Partial Observations | 3 | 0.62 | 2015 |
Holistic Measures for Evaluating Prediction Models in Smart Grids | 16 | 0.94 | 2015 |
Estimating Reduced Consumption for Dynamic Demand Response. | 2 | 0.39 | 2015 |
Prediction models for dynamic demand response: Requirements, challenges, and insights | 7 | 0.56 | 2015 |
Challenge: On Online Time Series Clustering for Demand Response: Optic - A Theory to Break the 'Curse of Dimensionality' | 0 | 0.34 | 2015 |
Enabling Automated Dynamic Demand Response: From Theory to Practice | 1 | 0.37 | 2015 |
Addressing data veracity in big data applications | 0 | 0.34 | 2014 |
Energy management systems: state of the art and emerging trends | 41 | 2.56 | 2013 |
Cloud-Based Software Platform for Big Data Analytics in Smart Grids | 5 | 0.54 | 2013 |
Toward data-driven demand-response optimization in a campus microgrid | 7 | 2.52 | 2011 |
Improving Energy Use Forecast for Campus Micro-grids Using Indirect Indicators | 20 | 3.44 | 2011 |
Using Roget's Thesaurus for Fine-grained Emotion Recognition. | 26 | 1.16 | 2008 |
Identifying expressions of emotion in text | 97 | 3.96 | 2007 |