随机变量模拟数据的产生算法设计与实现

Algorithm Design and Implementation of Random Variable Simulation Data

随机数在现代技术中,特别是在经济管理、系统仿真、人工智能等领域起着极其重要的作用。根据不同的应用场景、不同的应用需求,需要得到满足一定特定分布的系列随机数。但由于总体分布的特征差异较大,很难找到一个统一的随机变量产生方法。本文根据不同的分布特征,对工程技术应用的不同领域常用的随机分布,结合它们的分布函数及密度函数的特点,给出了产生随机数序列的相应算法,并通过Python语言在计算机上对所设计出来的算法进行模拟。实验结果表明,尽管不同分布的随机数产生方法有各自的优缺点,但是通过这些算法而产生的随机数符合相应概率分布的要求。

Random number plays an extremely important role in modern technology,especially in economic management,system simulation,artificial intelligence and other fields.It is necessary to obtain a series of random number that satisfy a certain distribution according to different application and requirements.However,due to the large differences in the characteristics of the overall distribution,it is difficult to find a uniform random variable generation method.Therefore,this paper proposes an algorithm for generating random number sequences that according to different distribution characteristics,based on the random distribution in different fields of engineering application,combined with the characteristics of their distribution functions and density functions,the designed algorithm is simulated on the computer through Python language.The experimental results show that although the random number generation methods of different distributions have their own advantages and disadvantages,the random number generated by these algorithms meets the requirements of the corresponding probability distribution.