Theory of Markov chain and its application in several representative examples

Markov chains can be widely used in a range of applied disciplines such as finance, physics, meteorology, chemistry, statistics, etc., which is not limited to theoretical mathematics. Markov chains were created by the Russian mathematician Markov and can be used to calculate the probability of various state transitions to each other, compared to many calculations in traditional probability calculations, Markov chains can be used to calculate the probability of each state transition easily, quickly, and accurately. Thus, Markov chains can be used to predict the probability of future events and in statistics to simulate complex distributions. In real life, Markov chains can be used to predict some impending disasters, such as tsunamis, earthquakes, and even the spread of diseases. If these are successfully predicted, the loss of life and property caused by these disasters could be greatly reduced. Moreover, the calculation method of the transfer matrix of the Markov chain is very suitable for the computing characteristics of artificial intelligence, so the convenience of using the Markov chain will be greatly increased.