Markov Chains
Markov Chains
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DOI：
10.1007/978-3-319-97412-5_3
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发表时间：
2019-04
期刊：
影响因子：
--
通讯作者：
Richard Lockhart;Simon Fraser
中科院分区：
文献类型：
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作者：
Richard Lockhart;Simon Fraser
问题1.农民乔治不相信天气预报员，他希望自己来预报天气。凭借多年的耕作经验，他观察到某些天气模式总是成立的。他把天气分为三类：晴天、多云和下雨。为了简化模型，Farmer George假设，如果他知道今天的天气，他可以完美地预测明天天气的分布。如果有一天天气晴朗，那么有80%的可能性是晴朗的，10%的可能性是多云的，10%的可能性是第二天下雨。如果天气多云，Farmer George认为第二天我们同样有可能看到晴天、多云或下雨的天气。最后，如果某一天下雨，有25%的可能性继续下雨，第二天天气多云的可能性为75%。
Problem 1. Farmer George does not believe in weather forecasters and wishes to predict the weather himself. With years of farming experience, he has observed that certain patterns for weather always hold to be true. He classifies weather into three categories: sunny, cloudy, and rainy. To simplify the model, Farmer George assumes that he can perfectly predict the distribution for the weather tomorrow, if he knows the weather today. If it’s sunny one day, there is a 80% chance it’s sunny, 10% chance it’s cloudy, and 10% chance it rains the next day. If it’s cloudy, Farmer George thinks there’s an equal chance we see sunny, cloudy, or rainy weather the following day. Lastly, if it’s raining on one day, there is a 25% chance that rain continues and a 75% chance the weather is cloudy the next day.