[curo]

Hopefully I understand your problem correctly...

You can use window functions to do things like dense rank, rank, percentiles, etc on each parameter in order to normalize the data. E.g., this one is at the 63rd percentile in size, 20th in distance, etc. This doesn't work so well if you have lots of 0s in your data.

Or you can find the min and max of each and divide by the max. This one is 42% of max, etc.

In each case you're trying to normalize diff parameters to represent something comparable (x/max, percentile, etc) so you can combine them. You can also do intermediate operations like take the logs or take the z score if you're trying to muffle the effects of outliers.

[esflow]

Thanks a lot, I will try it and test how well it works.