问题描述
我在寻找一种算法,或例如材料研究为predicting基于已知模式未来的事件。或许有这个名字,我只是不知道/记得了。这东西一般可能不存在,但我不是数学或算法的高手,所以我在这里要求的方向发展。
I'm looking for an algorithm or example material to study for predicting future events based on known patterns. Perhaps there is a name for this, and I just don't know/remember it. Something this general may not exist, but I'm not a master of math or algorithms, so I'm here asking for direction.
一个例子,我的理解是这样的:
An example, as I understand it would be something like this:
一个静态的事件发生在1月1日,2月1日,3月3日,4月4日。一个简单的解决办法是平均的日/时/分/每次出现的东西,这个数字增加至最后为人所知的发生,并有prediction。
A static event occurs on January 1st, February 1st, March 3rd, April 4th. A simple solution would be to average the days/hours/minutes/something between each occurrence, add that number to the last known occurrence, and have the prediction.
我是什么要求,或者是我应该学习?
What am I asking for, or what should I study?
有一点没有特定的目标,或任何特定变量来解释。这是一个简单的个人的思想,并有机会对我来说,学习新的东西。
There is no particular goal in mind, or any specific variables to account for. This is simply a personal thought, and an opportunity for me to learn something new.
推荐答案
我觉得有些话题可能是值得探讨包括的,特别是内插,外插和回归。
I think some topics that might be worth looking into include numerical analysis, specifically interpolation, extrapolation, and regression.
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