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Hidden Markov Model (HMM)

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Hidden Markov Model (HMM)  VIDEO LINK:  https://youtu.be/YIGCWNG8BIA A Hidden Markov Model (HMM) is a statistical model in which the system has hidden states that cannot be directly observed, but produce observable outputs. It is based on the Markov property, meaning the next state depends only on the current state. Video Chapters: HMM in Artificial Intelligence 00:00 Introduction 00:31 Statistical Model 00:54 HMM Examples 02:30 HMM 03:10 HMM Components 05:23 Viterbi Algorithm 06:23 HMM Applications 06:38 HMM Problems 07:28 HMM in Handwriting Recognition 11:20 Conclusion  HMM COMPONENTS A Hidden Markov Model (HMM) is a statistical model in which the system has hidden states that cannot be directly observed, but produce observable outputs. It is based on the Markov property, meaning the next state depends only on the current state. An HMM consists of states, observations, transition probabilities, emission probabilities, and initial probabilities. It is commonly used in a...

No Free Lunch Theorem for Optimization |Metaheuristic Optimization Algorithm

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No Free Lunch Theorem for Optimization No Free Lunch Theorem for Optimization According to No Free Lunch Theorem "There is no universal better algorithm exist that can solve all types of optimization problems". Today, Metaheuristic Optimization Algorithms are used in different areas to solve complex real work optimization problems. For example in Industrial Areas, Operation Research, Medical Field, Engineering design and other as you can see below:  History of Metaheuristic Optimization Algorithms: Genetic Algorithms (G.A.) - 1960's - 1970's Simulated Annealing (S.A.) - 1983 Tabu Search (T.S.) - 1986 Ant Colony Optimization Algorithm - 1992 Particle Swarm Optimization Algorithm - 1995 Differential Evolution (D.E.) -1997 Harmony Search (H.S.) - 2001 Honey Bee Algorithm (H.B.A.) - 2004 Artificial Bee Colony (A.B.C.) - 2005 ... Battle Royal Optimization Algorithm (B.R.O.A.) - 2020 In 1997, D.H. Wolpher and W. G. Macready published No Free Lunch Theorem for optimization. ...
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