Search results
Results from the WOW.Com Content Network
Example of the selection of a single individual. Fitness proportionate selection, also known as roulette wheel selection or spinning wheel selection, is a selection technique used in evolutionary algorithms for selecting potentially useful solutions for recombination. [1]
A SWB generator is the basis for the RANLUX generator, [19] widely used e.g. for particle physics simulations. Maximally periodic reciprocals: 1992 R. A. J. Matthews [20] A method with roots in number theory, although never used in practical applications. KISS: 1993 G. Marsaglia [21] Prototypical example of a combination generator. Multiply ...
Dice are an example of a mechanical hardware random number generator. When a cubical die is rolled, a random number from 1 to 6 is obtained. Random number generation is a process by which, often by means of a random number generator (RNG), a sequence of numbers or symbols is generated that cannot be reasonably predicted better than by random chance.
Apple iWork Numbers, included with Apple's iWork '08 suite exclusively for Mac OS X v10.4 or higher. AppleWorks – for MS Windows and Macintosh. This is a further development of the historical Claris Works Office suite. WordPerfect Office Quattro Pro – for MS Windows. Was one of the big three spreadsheets (the others being Lotus 123 and Excel).
Wheel factorization with n = 2 × 3 × 5 = 30.No primes will occur in the yellow areas. Wheel factorization is a method for generating a sequence of natural numbers by repeated additions, as determined by a number of the first few primes, so that the generated numbers are coprime with these primes, by construction.
A prime sieve or prime number sieve is a fast type of algorithm for finding primes. There are many prime sieves. The simple sieve of Eratosthenes (250s BCE), the sieve of Sundaram (1934), the still faster but more complicated sieve of Atkin [1] (2003), sieve of Pritchard (1979), and various wheel sieves [2] are most common.
the interrupts, mixing CPU cycle counter, kernel timer value, IRQ number, and instruction pointer of the interrupted instruction into a "fast pool" of entropy; the random-time I/O (events from keyboard, mouse, and disk), mixing the kernel timer value, cycle counter, device-specific information into the "input pool".
It can be shown that if is a pseudo-random number generator for the uniform distribution on (,) and if is the CDF of some given probability distribution , then is a pseudo-random number generator for , where : (,) is the percentile of , i.e. ():= {: ()}. Intuitively, an arbitrary distribution can be simulated from a simulation of the standard ...