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A model to predict water depth data from rainfall radar information.
https://github.com/sbrl/research-rainfallradar
Starbeamrainbowlabs
8a9cd6c1c0
I *really* hope this works. This is the 3rd major revision of this model. I've learnt a ton of stuff between now and my last attempt, so here's hoping that all goes well :D The basic idea behind this attempt is *Contrastive Learning*. If we don't get anything useful with this approach, then we can assume that it's not really possible / feasible. Something we need to watch out for is the variance (or rather lack thereof) in the dataset. We have 1.5M timesteps, but not a whole lot will be happening in most of those.... We may need to analyse the variance of the water depth data and extract a subsample that's more balanced. |
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| aimodel/src | ||
| rainfallwrangler | ||
| .gitignore | ||
| README.md | ||
Rainfall Radar
A model to predict water depth data from rainfall radar information.
This is the 3rd major version of this model.
rainfallwrangler
rainfallwrangler is a Node.js application to wrangle the dataset into something more appropriate for training an AI efficiently. The rainfall radar and water depth data are considered temporally to be regular time steps. Here's a diagram explaining the terminology:
NOW
│ │ │Water depth
│▼ Rainfall Radar Data ▼│[Offset] │▼
├─┬─┬─┬─┬─┬─┬─┬─┬─┬─┬─┬─┼─┬─┬─┬─┬─┼─┐
│ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │
│ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │
│ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │
│ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │
└─┴─┴─┴─┴─┴─┴─┴─┴─┴─┴─┴─┼─┴─┴─┴─┴─┴─┘
│
◄────────── Timesteps ─────────────►