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Algorithms Behind Space Missions ~xRay Pixy

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Learn different algorithms used in Space Missions. Video Link Video Chapters: Algorithms Behind Space Missions 00:00 Introduction 00:52 Space Missions 04:26 Space Missions Challenges 07:04 Algorithms Used in Space Missions 10:36 Optimization Techniques 11:44 Conclusion  NASA conducts space missions to explore the universe for various scientific, technological, and practical reasons: Understanding Our Place in the Universe Search for Life Beyond Earth Studying Earth from Space Advancing Technology Supporting Human Exploration Resource Utilization Inspiring Humanity Examples of NASA Space Missions Apollo Program: Sent humans to the Moon (1969–1972). Mars Rovers (Spirit, Opportunity, Perseverance): Explored Mars' surface and geology. Voyager Missions: Studied the outer planets and interstellar space. Hubble Space Telescope: Captured breathtaking images of the universe. International Space Station (ISS): Supports research in microgravity and international collaboration. Different ...
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Grey Wolf Optimization Algorithm Numerical Example

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 Grey Wolf Optimization Algorithm Numerical Example Grey Wolf Optimization Algorithm Steps 1.) Initialize Grey Wolf Population. 2.) Initialize a, A, and C. 3.) Calculate the fitness of each search agent. 4.) 𝑿_𝜶 = best search agent 5.) 𝑿_𝜷 = second-best search agent 6.) 𝑿_𝜹 = third best search agent. 7.) while (t<Max number of iteration) 8.) For each search agent       update the position of the current search agent by the above equations end for 9.) update a, A, and C 10.) Calculate the fitness of all search agents. 11.) update 𝑿_𝜶, 𝑿_𝜷, 𝑿_𝜹 12.) t = t+1 end while 13.) return 𝑿_𝜶 Grey Wolf Optimization Algorithm Numerical Example STEP 1.  Initialize the Grey wolf Population [Initial Position for each Search Agent] 𝒙_(𝒊  )  (i = 1,2,3,…n)     n = 6 // Number of Search Agents  [ -100, 100] // Range Initial Wolf Position      3.2228     4.1553    -3.8197     4.2330  ...
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Grey Wolf Optimization Algorithm

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 Grey Wolf Optimization Algorithm  (GWO) Grey Wolf Optimization Grey Wolf Optimization Algorithm is a metaheuristic proposed by Mirjaliali Mohammad and Lewis, 2014. Grey Wolf Optimizer is inspired by the social hierarchy and the hunting technique of Grey Wolves. What is Metaheuristic? Metaheuristic means a High-level problem-independent algorithmic framework (develop optimization algorithms). Metaheuristic algorithms find the best solution out of all possible solutions of optimization. Who are the Grey Wolves? Wolf (Animal): Wolf Lived in a highly organized pack. Also known as Gray wolf or Grey Wolf, is a large canine. Wolf Speed is 50-60 km/h. Their Lifespan is 6-8 years (in the wild). Scientific Name: Canis Lupus. Family: Canidae (Biological family of dog-like carnivorans). Grey Wolves lived in a highly organized pack. The average pack size ranges from 5-12.  4 different ranks of wolves in a pack: Alpha Wolf, Beta Wolf, Delta Wolf, and Omega Wolf. How Grey Wolf Optimiza...
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