Hidden Markov Model - Applications, Strengths, and Weaknesses

The Hidden Markov Model is widely used in weather forecasting, Bioinformatics, disease diagnosis, signal processing, stock market, interpretation of clinical results, etc. The model provides probabilistic information and a good interpretation of the outcome meanwhile producing the best results. This paper studies the applications, advantages, and limitations of the Hidden Markov Model across various fields. The study suggests that with accurate calculation and precise input, the Hidden Markov Model will work wonderfully well with high accuracy, though its application areas are limited. Besides this, the main drawback of the model is its computational expensiveness and probabilistic results. Furthermore, the work also suggests a scope for further exploring the applications of Hidden Markov Model in enhancing the security of a nation.