Bayesian Support Vector Machine (BSVM)
A machine learning based approach is developed to detect events that have rarely been seen in the historical data. The data can include building energy consumption, sensor data, environmental data and any data that may affect the building's energy consumption. The algorithm is a modified nonlinear Bayesian support vector machine, which examines daily energy consumption profile, detect the days with abnormal events, and diagnose the cause of the events.
- Short Name / Acronym:
- BSVM
- Project Type:
- Open Source, No Publicly Available Repository
- Site Accession Number:
- 7452; Battelle IPID 30793
- Software Type:
- Scientific
- License(s):
- BSD 2-clause "Simplified" License
- Programming Language(s):
- Matlab R2014a
- Research Organization:
- Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
- Sponsoring Organization:
- USDOEPrimary Award/Contract Number:AC05-76RL01830
- DOE Contract Number:
- AC05-76RL01830
- Code ID:
- 55006
- OSTI ID:
- 1352158
- Country of Origin:
- United States
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