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Poplar Optimization Algorithm || Step-By-Step || ~xRay Pixy

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The Poplar Optimization Algorithm (POA) is a nature-inspired optimization method based on how poplar trees reproduce. It uses sexual propagation (seed dispersal by wind) for exploration and asexual reproduction (cutting and regrowth) for exploitation. Mutation and chaos factors help maintain diversity and prevent premature convergence, making POA efficient for solving complex optimization problems. Learn the Poplar Optimization Algorithm Step-By-Step using Examples. Video Chapters: Poplar Optimization Algorithm (POA) 00:00 Introduction 02:12 POA Applications 03:32 POA Steps 05:50 Execute Algorithm 1 13:45 Execute Algorithm 2 16:38 Execute Algorithm 3 18:15 Conclusion Main Points of the Poplar Optimization Algorithm (POA) Nature-Inspired Algorithm – Based on the reproductive mechanisms of poplar trees. Two Key Processes : Sexual Propagation (Seed Dispersal) – Uses wind to spread seeds, allowing broad exploration. Asexual Reproduction (Cuttings) – Strong branches grow ...
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Sperm Swarm Optimizer || Step-By-Step || ~xRay Pixy

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Sperm Swarm Optimizer (SSO) || Step-By-Step || ~xRay Pixy Video Link Click Here:   SSO Learn Sperm Swarm Optimizer Step-By-Step Using Examples. Video Chapters: Sperm Swarm Optimizer 00:00 Introduction 01:20 Topic Covered 01:41 Fertilization Process 07:02 Sperm Swarm Optimizer Simulation 10:14 Sperm Swarm Optimizer Steps 15:27 Conclusion The Sperm Swarm Optimization (SSO) algorithm is a method inspired by how sperm move toward an egg during fertilization.  Swarm Movement : Each sperm (candidate solution) is represented as a point in a multidimensional search space. The sperms work together to find the best solution (the egg). Each sperm's position (location) is adjusted based on its current velocity, its personal best, and the global best.The algorithm keeps updating positions and velocities until an optimal solution is found or a stopping condition is met. Exploration and Exploitation : Exploration: Randomized factors (pH and temperature) allow wide search. Exploitat...
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Nash Equilibrium In Game Theory ~xRay Pixy

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 Video Link  CLICK HERE... Learn Nash Equilibrium In Game Theory Step-By-Step Using Examples. Video Chapters: Nash Equilibrium  00:00 Introduction 00:19 Topics Covered 00:33 Nash Equilibrium  01:55 Example 1  02:30 Example 2 04:46 Game Core Elements 06:41 Types of Game Strategies 06:55  Prisoner’s Dilemma  07:17  Prisoner’s Dilemma Example 3 09:16 Dominated Strategy  10:56 Applications 11:34 Conclusion The Nash Equilibrium is a concept in game theory that describes a situation where no player can benefit by changing their strategy while the other players keep their strategies unchanged.  No player can increase their payoff by changing their choice alone while others keep theirs the same. Example : If Chrysler, Ford, and GM each choose their production levels so that no company can make more money by changing their choice, it’s a Nash Equilibrium Prisoner’s Dilemma : Two criminals are arrested and interrogated separately. Each has two ...
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Firefly Algorithm In Hindi ~xRay Pixy

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Learn Firefly Algorithm Step-By-Step using Numerical Examples. Video Chapters: Firefly Algorithm 00:00 Introduction 00:40 Topics Covered 01:01 Firefly Algorithm 01:42 Firefly Algorithm Applications 01:57 Firefly Algorithm Working 03:50 Firefly Algorithm Mathematical Models 05:52 Firefly Algorithm Step-By-Step 13:58 Firefly Algorithm Advantages & Limitations 14:29 Conclusion Firefly Algorithm In Hindi ~xRay Pixy Click here  Video Link The Firefly Algorithm (FA) is a nature-inspired optimization algorithm developed by Xin-She Yang in 2008. It mimics the behavior of fireflies, specifically their flashing patterns, which are used for attracting mates or prey. Firefly Algorithm Core Concept Attraction : The attractiveness of a firefly is proportional to its brightness. A brighter firefly attracts less bright fireflies. Brightness : The brightness is associated with the fitness of the solution at a firefly's position. Movement : A less bright firefly moves toward a brighter firefly....
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Chernobyl Disaster Optimizer || Step-By-Step || ~xRay Pixy

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Chernobyl Disaster Optimizer || Step-By-Step || ~xRay Pixy VIDEO LINK... Learn the Chernobyl disaster optimizer (CDO) Step-By-Step using Examples. Video Chapters: Chernobyl Disaster Optimizer (CDO) 00:00 Introduction 02:05 Chernobyl Disaster Optimizer  02:31 Topics Covered 02:05 Chernobyl Disaster || How Chernobyl Disaster Happened?  05:40 3 Radiation Released after Chernobyl Disaster  07:35 How CDO Simulates Chornobyl Nuclear Disaster 09:44 How particle attack models Mathematically 10:44 CDO Step-By-Step  14:52 Conclusion On April 26, 1986, Reactor 4 at the Chernobyl Nuclear Power Plant in Ukraine had a test while running at low power. Things went wrong, causing an explosion and a fire that destroyed the reactor. This accident released a huge amount of radiation into the air, affecting many people and the environment. Key Isotopes Released in the Chernobyl Disaster: Iodine-131 : Short-lived but highly radioactive; primarily affects the thyroid gland. Cesium-137 : Lo...
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