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Intelligent Traffic Management Using || AI & Metaheuristics || ~xRay Pixy

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Hybrid Artificial Intelligence and Metaheuristics for Smart City TRafci Management Problem Video Chapters: 00:00 Introduction 00:40 Smart Cities 01:14 Traditional Methods for Traffic Management 02:12 Hybrid Approach AI and Metaheuristics 02:47 STEPS for Hybrid  Traffic Management System 08:40 Advantages of Smart Traffic Management System 09:33 Conclusion

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 Discrete Variable Comb
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