Search results
Results from the WOW.Com Content Network
The sequential elimination methods are a class of voting systems that repeatedly eliminate the last-place finisher of another voting method until a single candidate remains. [1] The method used to determine the loser is called the base method .
The Schreier–Sims algorithm is an algorithm in computational group theory, named after the mathematicians Otto Schreier and Charles Sims.This algorithm can find the order of a finite permutation group, determine whether a given permutation is a member of the group, and other tasks in polynomial time.
Default generator in R and the Python language starting from version 2.3. Xorshift: 2003 G. Marsaglia [26] It is a very fast sub-type of LFSR generators. Marsaglia also suggested as an improvement the xorwow generator, in which the output of a xorshift generator is added with a Weyl sequence.
Random assignment or random placement is an experimental technique for assigning human participants or animal subjects to different groups in an experiment (e.g., a treatment group versus a control group) using randomization, such as by a chance procedure (e.g., flipping a coin) or a random number generator. [1]
In fact, it is NP-complete to decide whether a given candidate is a Baldwin winner, i.e., whether there exists an elimination sequence that leaves a given candidate uneliminated. [ 11 ] Both methods are computationally more difficult to manipulate than Borda's method.
For these applications, truly random numbers are ideal, and very high quality pseudo-random numbers are necessary if truly random numbers, such as coming from a hardware random number generator, are unavailable. Truly random numbers are absolutely required to be assured of the theoretical security provided by the one-time pad — the only ...
Instant-runoff voting (IRV; US: ranked-choice voting (RCV), AU: preferential voting, UK/NZ: alternative vote) is a single-winner, multi-round elimination rule that uses ranked voting to simulate a series of runoff elections.
Sudoku can be solved using stochastic (random-based) algorithms. [11] [12] An example of this method is to: Randomly assign numbers to the blank cells in the grid. Calculate the number of errors. "Shuffle" the inserted numbers until the number of mistakes is reduced to zero. A solution to the puzzle is then found.