Problem
Pattern and Anomaly Detection
The client belongs to the energy industry and power outages and restoration are a huge problem across the industry. They want to be able to detect any patterns or anomalies in the power distribution grid in order to be able to take preventive and restoration steps efficiently.
Technology Used
Python, SQL (for data extraction)
Solution
The problem of pattern and anomaly detection was solved with the use of unsupervised learning technique Self Organizing Maps. This machine learning model was successful in leveraging AMI voltage data and meter events to identify anomalies and minimize risk on electric distribution grid.
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