by Outcast_Searcher » Fri 01 Jun 2012, 05:50:43
$this->bbcode_second_pass_quote('dinopello', ' ')I think there are a lot of factors that will still require the numerical approach for real-world applications.
To anyone who has had much college level math, isn't this rather obvious?
The "numerical analysis" class I took in college in '80, if memory serves, was highly recommended by my computer science advisor as being one of the more practical problem-solving courses a computer geek like me could take. Especially given that I dropped my math minor due to advanced calculus being more than I was willing to put up with (seemed to be proving all the stuff we learned in 3 semesters of calculus -- I'd rather have wounds closed without anesthetic, thank you).
All kinds of cool practical numerical analysis tools, like using cubic splines for curve fitting worked wonders when traditional strictly analytic methods were way beyond us (at least at the undergraduate level). And that was over 30 years ago.
Now that we have some awareness of the incredible complexity of the natural world via chaos theory, the need for practical numerical analysis should be blindingly obvious, and (I presume) very commonly used. (For example, despite all the recent additional complexity for weather prediction models -- look how inaccurate thunderstorm predictions are over the summer for the typical midwestern American city. And that's just one day forecasts. Now go out over 3 days, and the weather predictions bear little resemblence to reality).
Try finding a strictly analytic solution to THAT problem. Not likely.
I think I agree with the posts above that though this is a nice accomplishment, it will likely have limited PRACTICAL implications. Dealing with chaotic natural issues, like weather, is a necessary inconvenience when air resistance issues come into play in the real world.
Given the track record of the perma-doomer blogs, I wouldn't bet a fast crash doomer's money on their predictions.