| Математически - корреляционный метод предсказания. ID:20383 |
Чт, 5 октября 2006 22:32 [#] [») |
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Прогуливаясь, по иностранным форумам о Рулетке наткнулся на математический метод предсказания.
Автор Rollo:
Lets talk about the math needed to predict the roulette ball, given measurements. Some people here have of course already developed a well proven formula, and I would be delighted to see what they have found out! What is really the algorithm in those roulette computers?
My first idea is simply the following:
Consider only two variables, S and V:
S is the distance which the ball will roll until it hits the wheel.
V is the speed of the ball at any given point in time, relative to the wheel. Actually, it is the speed at the point in time between the two times when its position is clocked.
Units for both variables are suitably given in terms of "pockets" (i.e. the 37 numbered landing pockets) on the wheel. Position is defined as the pocket which the ball is closest to. Distance as the number of pockets between two positions. Speed as the number of pockets passed by per second.
Measure V and observe the S that follows at many occasions for any specific roulette wheel. Then correlate V and S, i.e. fit a function which minimizes the sum of squered differences from the observed points in the S and V plot. Estimate k in: S = k*V.
Then when the speed is measured, multiply it with the konstant k and viola there is an estimation of S!
It can be a very good idea to extimate k-values for root of V and for V squared too and see which gives the best fit, since there probably is a non-linear acceleration involved. Do the regression S = k*V + c*squareroot[V] + q*V^2 and see which of k, c and q are significant.
Now, do you think that this simple approach is the best? Or how could it be improved? Note that I do not really care about the physics and mecanichs of a ball rolling and jumping. I just do the statistics an let everything between input and output remain a black box.
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