Machine learning drives EV adoption insights.

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Machine Learning and Artificial Intelligence Inform EV Adoption Levels

One of the largest challenges with managing large datasets is ensuring they are complete. Many use cases can use machine learning (ML) and artificial intelligence (AI) algorithms to accurately identify and fill gaps of unknown historical data sets with data extrapolated from other data sources. We recently put this to the test by analyzing electric vehicle (EV) adoption levels in the U.S. and identifying which states and regions have (or will have) high and low EV adoption. See how Altair’s data analytics solutions rose to the challenge.

U.S. EV Adoption: Feast or Famine?

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Can Data Analytics Put You Behind the Wheel of an Electric Vehicle?

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Electric Vehicle Adoption

Interactive Map

With EV adoption data available for only 15 states, Altair’s predictive data modeling technology applied machine learning to impute the missing data to show complete EV adoption levels across the U.S.

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Predict and Visualize EV Adoption

Learn the process and findings behind how Altair's data analytics products were used to investigate (and predict) the adoption level of electric vehicles in the U.S.

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