Week 6 – Mild Improvement

Apr 24, 2020

Hey all,

I have completed, or sufficiently optimized, my work with the training data (An arbitrary 80% of roadways from the study),  and with that comes joy accompanied by ambition for further improvement—  a sentiment shared by the general public, who now have an excuse to stay at least six feet away from me at all times.

I’m also re-reading a similar paper that addresses climate as a factor in pavement damage, though the heavy lifting seems to have been done by traditional statistical analysis as opposed to machine learning, which makes for some difficulty in understanding the isolation of a single variable affecting the pavement. It’s also a voluminous 260 pages long, and while it maintains density akin to that of a shorter paper, I’m only looking for a couple needles in a veritable haystack.

Even if I do manage to come up with some percentage of damage caused by load bearing vehicles, I sometimes wonder how that information would be implemented to make the world a better, or at least a more efficient, place. Something I need to consider in the following weeks.

Stay safe,



3 Replies to “Week 6 – Mild Improvement”

  1. Alan Y. says:

    Glad to hear you are making progress! Good luck with this next challenge.

  2. johnh says:

    I agree that what to do with the info is perhaps the most interesting part. Fewer load-bearing vehicles is probably not happening. Maybe what we need is better roads, like self-healing asphalt?

  3. Lieselotte D. says:

    Maybe the percentage of damage done by load-bearing vehicles can be used in calculations to determine when and where the roads need to be repaired. I’m thinking of it in terms of statistics, like where these vehicles are most likely to travel and how often, and using that to create a more efficient maintenance schedule. I’m interested to see what you come up with.

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