conEdison

conEdison

conEdison

conEdison logoCurrent and recent Con Edison projects illustrate how the Center is applying machine learning to crucial challenges confronted by the public utility providing electricity and gas to the New York City metropolitan area.

Con Edison Projects - Secondary Events

An actionable real-world machine learning project which uses NLP, data cleaning and management and involves specific domain knowledge.

Our goal is to rank the electricity service structures (manholes and service boxes) in Manhattan, Brooklyn, Bronx, and Queens according to their vulnerability to serious manhole events such as manhole fires, explosions and smoking manholes.

Columbia Decision Support System for the Manhattan Electric Control Center (MECC) 2005

Columbia Decision Support System for the Manhattan Electric Control Center (MECC) 2005

Columbia Decision Support System for the Manhattan Electric Control Center (MECC) 2005
Contract with Consolidated Edison.
Senior Team Members: Roger Anderson, David Waltz, Albert Boulanger, Phil Long

For more information, see article by Columbia’s Earth Institute, available online at http://www.earthinstitute.columbia.edu/news/2005/story06-01-05e.html

Columbia Learning System for Prioritization of Feeders for Long-Term Replacement Program for Cable and Splice Center of Excellence

Columbia Learning System for Prioritization of Feeders for Long-Term Replacement Program for Cable and Splice Center of Excellence

Columbia Learning System for Prioritization of Feeders for Long-Term Replacement Program for Cable and Splice Center of Excellence. Contract with Consolidated Edison.
Senior Team Members: Roger Anderson, David Waltz, Albert Boulanger, Phil Long

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