Time Series Clustering for Monitoring Fueling Infrastructure Performance with Kalai Ramea - #300

The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence) - Podcast tekijän mukaan Sam Charrington

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Today we're joined by Kalai Ramea, Data Scientist at PARC, a Xerox Company. In this episode we discuss her journey buying a hydrogen car and the subsequent journey and paper that followed assessing fueling stations. In her next paper, Kalai looked at fuel consumption at hydrogen stations and used temporal clustering to identify signatures of usage over time. As the number of fueling stations is planned to increase dramatically in the future, building reliability on their performance is crucial.

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