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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...

ANT COLONY OPTIMIZATION ALGORITHM STEP-BY-STEP WITH EXAMPLE

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 Ant colony optimization algorithms Do you know: How the Ant Colony Optimization algorithm works?   We all know about ants. Researchers have estimated about 13800 known ant species. In an ant colony, there is Queen (i.e., female ant), fertilized male ant (also known as drone), female ant workers, and soldiers. Queen ant can live up to 30 years. Ants live in colonies (also known as ant nest). An average ant colony contains 1000 individual ants and an ant super colony can contain 300 million individual ants. Ants communicate with each other indirectly using pheromones, sound, and touch. Ant colony optimization is a Nature Inspired Population Based Metaheuristic Optimization Algorithm. Ant colony optimization (ACO) is inspired by the real ant food searching behavior. Ant colony optimization algorithm is basically inspired by the pheromone-based ant communication . Ant colony optimization is developed by Marco Dorigo in 1992.  Author developed this algorithm to solve Dis...
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