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Received:March 18, 2020
Received:March 18, 2020
中文摘要: 隐马尔可夫模型在语音识别、自然语言处理、生物信息、模式识别等领域有着广泛的应用。介绍了隐马尔可夫模型的基本概念，分别叙述了隐马尔可夫模型的概率计算算法、学习算法以及预测算法。利用观测的海藻湿度数据作为训练数据，找出隐藏的转换概率，构建了隐马尔可夫模型，完成了预测天气变化的机器学习。
Abstract:Hidden Markov model is widely used in speech recognition,natural language processing,biological information,pattern recognition and other fields.This paper first introduces the basic concept of hidden Markov model,and then describes the probability calculation algorithm,learning algorithm and prediction algorithm of hidden Markov model.Using the observed seaweed humidity data as the training data,we can find out the hidden conversion probability,and build the hidden Markov model and complete the machine learning of forecasting weather changes.
keywords: training data observation probability matrix prediction model probability calculation learning algorithm
文章编号：20215009 中图分类号：TP312 文献标志码：
基金项目:
| Author Name | Affiliation | |
| LIU Hui | School of Computer Science and Technology, Shanghai University of Electric Power, Shanghai 200090, China | hlliuhui@sina.com |
| Author Name | Affiliation | |
| LIU Hui | School of Computer Science and Technology, Shanghai University of Electric Power, Shanghai 200090, China | hlliuhui@sina.com |
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