seed for random number generator

Method 1(Data Type) (minimum value + math. Random () * (maximum value-Minimum value + 1 ))Example:(INT) (1 + math. Random () * (10-1 + 1 ))INT-type numbers from 1 to 10Method 2Obtain Random NumberFor (INT I = 0; I {System. Out. println (INT) (1 +

This paper mainly introduces 3 kinds of methods of obtaining random number in Java, mainly using random () function to realize Method 1 (data type) (Minimum +math.random () * (maximum-min +1)) Example: (int) (1+math.random () * (10-1+1))

Sourcehttps://blogs.unity3d.com/cn/2015/01/07/a-primer-on-repeatable-random-numbers/(English version)Http://www.manew.com/thread-37144-1-1.htmlNo matter what kind of program you create, you can almost do without random numbers. If you want to

There is no real random number generator in the computer, but it can make the generated digital repetition rate very low, it seems like a real random number, to achieve this function ProgramIt is called a pseudo-random number generator. There are

There is no real random number generator in the computer, but it can make the resulting digital repetition rate very low, so it looks like a real random number, the program to achieve this function is called pseudo-random number generator.There are

RandomThe random class in Java generates a pseudo-random number, uses the seed of 48-bit, and then calls a linear congruential formula linear congruence equation (Donald Knuth's programming Art of 3.2.1)If two random instances use the same seed, and

Introduction to linear homogeneous random number generator: The old LCG (linear congruential generator) represents the best and simplest pseudo-random number generator algorithm. The main reason is that it is easy to understand, easy to implement,

pseudo-Random (preundorandom): Random numbers generated by the algorithm are pseudo-random!! only random numbers generated by real random events are really random!! For example, random numbers are generated through the machine's hardware noise,

The random class is used in Java for the resulting stochastic number, new Random (10): 10 is the number of seeds. Note: One of the characteristics of random is that random objects of the same seed number are exactly the same as those generated by

In the previous blog, we learned about the real random number generator based on physical phenomena, however, the real random number generation is slow, for the actual computation needs, the random number in the computer is generated by the program