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And if there are no roots, where would you advise?
there's a new idea about the equation.
0.998683^x + 1.00216908^u+ 1.002040888^z+ 0.998182^e+ 1.003999^k=1
I think the doctor already knows what I'm getting at)
there's a new idea about the equation.
0.998683^x + 1.00216908^u+ 1.002040888^z+ 0.998182^e+ 1.003999^k=1
then the selection can also be done depending on the targets), I will try a couple of thoughts to calculate
http://newfiz.narod.ru/gra-opus.htm
Therefore, with grief resort to curve methods. In simple way it is called "through ass", and in scientific way - "optimization of many parameters". Few people know what the beauty of this method is. There, it happens that in a stream of experimental data there are some features which are superfluous for theoretical reasons. Then the problem is easily solved: there is a set of mathematical procedures - filtering, smoothing, etc. - which allow to remove all unnecessary nonsense from the data stream. It is not a difficult thing: to remove it. But what poor scientists have to do in the opposite situation: when a certain feature is stubbornly missing from the data stream - but they really want it to be there? In such cases, a method of multi-parameter optimisation was developed. It is good in that it allows to testify quite scientifically the presence of nonexistent effects. For this purpose, complex, analytically unsolvable equations are written, in which the desired effect - this is the key point! - is treated as if it really exists. The more contrived the equations are, and the more parameters they include, the better. Because the more the sense of further "optimization" mystery becomes non-obvious to prying eyes. This mystery is as follows. With the help of high-speed computers, one varies the input parameters of equations in such a way to find the best agreement between the theory, which has the desired effect, and the experimental data, which do not have this effect. It may seem strange to someone unfamiliar - what kind of "best fit" can we talk about in such a case. Yes, the kind that works! Of course, here we have the best of the bad, but it is honestly the best! This is the sense of "optimization" - they did not run the computer for nothing, really! So, the computer will give out a packet of values of "optimized" parameters. And now let somebody from dear fellows try to doubt that the effect for which all this "optimization" was conceived really exists. How, they say, it does not exist, if it was taken into account in the theory and the best agreement of this theory with the experimental data was found!
And if there are no roots, where would you advise?
Same place. To find out if there are no roots. Read CHAGO, try different methods. None of them will find the roots if there are none.
I don't see how this war and peace text applies to me...
hehehe. like this:
... I think the doctor knows where I'm going with this)
There, too. To find out if there are no roots. Read CHYAGO, try different methods. None of them will find the roots if there are none.
I'd rather either just look at the function and think, or plot it and look at it. That's enough for me.
Heh-heh. Like this:
There's a suspicion of a bug, you need to double-check it, it looks like over-optimisation probably because you shoved the wrong data into the calculation, so maybe you have sensitivity to reference point. that's why I wrote about making clusters out of oscillator values.
There is a suspicion of a bug, you need to double-check it, it looks like over-optimisation probably because you shoved the wrong data into the calculation, so maybe you have sensitivity to reference point. that's why I wrote about making clusters out of oscillator values.