Continuous Markov Chain and its usage in Weather Forecasting
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A continuous Markov chain is like a never-ending game that helps us understand how something with a limited number of possible situations can change over time. Imagine a board game with different spaces for weather conditions (sunny, cloudy, or rainy), and the game is always moving between these spaces without taking turns.
This idea is useful in weather forecasting because it lets us predict the chances of different weather conditions happening in the future. We can look at past weather data to figure out how likely it is for the weather to change from one condition to another.
However, this method has some limits because it doesn’t consider things like where weather events happen and assumes that future weather only depends on what’s happening right now. More advanced models are often used to give more accurate weather forecasts, but continuous Markov chains can still be helpful for understanding general patterns and the chances of extreme weather events happening.
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