我试图了解有关 AnyLogic 源到达率的最佳实践.我知道指数和泊松是两种不同的概率分布.例如，当在 AnyLogic 中使用到达率"并选择 10 个/小时的速率时，这是否会以指数方式或根据泊松分布每小时生成 10 个代理，还是同样的事情?

I am trying to understand the best practices regarding AnyLogic's source arrival rates. I know that Exponential and Poisson are two different probability distributions. When using "Arrival Rate" in AnyLogic and choosing a rate of 10/hour for example, does this generate 10 agents per hour exponentially or according to a Poisson distribution or is it the same thing?

我真的需要指导来理解这方面的最佳做法.为了简化问题，如果按照泊松分布我的到达率为 10/小时，那么在 AnyLogic 中建模的正确方法是什么?

I really need guidance on understanding the best practices in this matter. To simplify the question, if I have an arrival rate of 10/hour following a Poisson distribution, what is the right way to model that in AnyLogic?

非常感谢！

在 AnyLogic 的任何源中，如果您选择一个比率，它将自动为泊松，其中您的比率将是泊松分布的 lambda 参数... this意味着平均每个时间单位生成的 lambda 代理

In any source in AnyLogic, if you choose a rate, it will automatically be poisson where your rate will be the lambda parameter of your poisson distribution... this means that in average you will get lambda agents per time unit generated

指数分布等价于泊松分布，只是它考虑了每次到达之间的时间.(这意味着您需要在源中使用由到达间隔时间定义的到达，否则没有多大意义)

The exponential distribution is equivalent to the poisson distribution, except that it takes into consideration the time between each arrival instead. (this means that you need to use arrivals defined by inter-arrival time in your source, otherwise it wouldn't make much sense)

每个时间单位的泊松 (lambda) 到达次数等于每次到达的指数 (lambda) 时间单位，您使用哪个并不重要

poisson(lambda) arrivals per time unit is equivalent to exponential(lambda) time units per arrival, it doesn't really matter which one you use