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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 ...

Transient Search Optimization Algorithm || Step-By-Step || ~xRay Pixy https://youtu.be/T2lVQ8mYFoM Video Chapters: TSO Algorithm 00:00 Introduction 00:44 Topics Covered 01:14 Transient Behavior 02:57 Transient Search Optimization Algorithm 06:10 TSOA Mathematical Models 10:30 TSOA Step-By-Step 15:32 TSOA Applications 15:58 TSOA Advantages 16:22 TSOA Disadvantages 16:28 Conclusion Evolutionary algorithms (EAs) are optimization methods inspired by the process of evolution in nature. They aim to find the best solutions to problems by mimicking natural selection and genetics. Key Steps in Evolutionary Algorithms : Start with a Population: Think of a population as a group of random guesses or potential solutions to your problem. Each "individual" in the population represents one solution. Evaluate Fitness: Just like in nature, some individuals are better suited to survive in their environment. In EAs, the "fitness" of a solution tells us how good it is at solving the pr...

Transient Search Optimization Algorithm || Step-By-Step || ~xRay Pixy Learn Transient Search Optimization Algorithm (TSOA) Step-by-step using examples. Video Chapters: TSO Algorithm 00:00 Introduction 00:44 Topics Covered 01:14 Transient Behavior 02:57 Transient Search Optimization Algorithm 06:10 TSOA Mathematical Models 10:30 TSOA Step-By-Step 15:32 TSOA Applications 15:58 TSOA Advantages 16:22 TSOA Disadvantages 16:28 Conclusion Transient Search Optimization Algorithm (TSOA) is a metaheuristic optimization technique inspired by the concept of transient behavior in physical or natural systems. In simple terms, it mimics how certain systems, like electrical circuits or natural phenomena, go through temporary changes (called transients) before settling into a stable state. What Happens in Electrical Circuits with Inductance and Capacitance? When you switch on or off a circuit containing inductors and capacitors, it doesn’t immediately settle into its final, stable state. Instead, it ...

V ehicle R outing P roblem Learn Vehicle Routing Problems Step-By-Step using Examples. Video Chapters: Vehicle Routing Problem (VRP) 00:00 Introduction 00:18 VRP Example 00:52 VRP Variants 02:43 VRP Objective 03:20 VRP Component 06:06 VRP Graph Representation 05:13 VRP Challenge 05:51 TSP vs VRP 07:17 VRP Real-Life Situations 07:38 VRP Solving Rules 08:57 VRP Method 09:16 Metaheuristics for VRP 10:16 VRP Application Areas 10:24 Metaheuristics to solve VRP 11:39 Conclusion VEHICLE ROUTING PROBLEM  is a fundamental combinatorial optimization and integer programming problem in the fields of transportation, logistics, and operations research. It involves determining the most efficient routes for a fleet of vehicles to traverse in order to deliver goods or services to a set of customers, subject to various constraints. Objective: Minimize the Total Route Cost. While satisfying all Co Capacity Constraint Time Window Constraints VRP Basic Components Depot: The starting and ending point f...

Learn Black Widow Optimization Algorithm Step-By-Step using Examples. Video Chapters: BWO Algorithm 00:00 Introduction 00:14 Topics Covered 00:31 BWO Algorithm INSPIRATION 01:01 About Black Widow Spider 02:53 Black Widow Spider BEHAVIOR 03:21 BWO Algorithm STEPS 13:22 Conclusion

ACO in Hindi Learn Ant Colony Optimization Algorithm (ACO) in Hindi. Video Chapters: ACO Algorithm 00:00 Introduction 00:27 Topics Covered 00:53 About Ant Colony Optimization 01:07 ACO Applications 01:57 ACO Inspiration  07:06 Real Ants Simulation as Artificial Ants 10:00 ACO Mathematical Models 10:26 ACO Steps 19:09 Conclusion How ACO Works Ant Colony Optimization is inspired by how real ants find the shortest path to food. Ants deposit pheromones on paths they travel, and other ants tend to follow paths with stronger pheromone trails. Over time, this leads to finding the most efficient route.  To explain the Ant Colony Optimization (ACO) applied to the Traveling Salesman Problem (TSP) in a simple and concise way within 2 minutes, here's an approach: Introduction to TSP The Traveling Salesman Problem asks: "Given a set of cities, find the shortest route that visits every city exactly once and returns to the starting point." How ACO Works Ant Colony Optimization is ins...

Learn how to implement an obstacle-avoiding path planning for a robot using the Grey Wolf Optimization (GWO) in a static environment. #optimization #algorithm #metaheuristic #robotics #deeplearning #ArtificialIntelligence #MachineLearning #computervision #research #projects #thesis #Python

Learn Path Planning in Robotics: Techniques, Algorithms, and Applications Video Chapters: Robot Path Planning using PSO 00:00 Introduction 00:14 Topics Covered  01:30 Robot Path Planning 03:07 Robot Classification Based on Configuration 04:28 Robot Classification Based on Performance 05:53 Importance of Robot Path Planning 08:19 Map Representation 09:29 Robot Path Planning Applications 10:21 Challenges in Robot Path Planning 11:51 Comparison Metaheuristics vs Traditional Methods for Path Planning 14:30 PSO for Robot Path Planning 19:00 Conclusion

Learn Particle Swarm Optimization (PSO) In Hindi  Video Chapters: PSO in Hindi 00:00 Introduction 00:58 Topics Covered 01:46 What is Optimization? 07:08 What is the PSO Algorithm? 07:48 PSO Inspiration 09:44 Particle Swarm Optimization Simulation  12:58 PSO Step-By-Step 23:06 PSO Challenges and Solutions 24:31 PSO Applications 24:51 Conclusion

Learn the Rat Swarm Optimization Algorithm Step-By-Step using the Example Video Chapters: Rat Swarm Optimizer 00:00 Introduction 00:16 Topics Covered 00:54 Algorithm Performance Analysis 01:18 Rat Swarm Optimizer 01:50 Rat's Behavior in Nature 03:19 Chasing Behavior 04:23 Fighting Behavior  05:29 RSO Mathematical Models 12:22 RSO Step-By-Step 18:04 RSO Advantages, Disadvantages, and Applications  20:18 Conclusion  #optimization #algorithm #metaheuristic #robotics #deeplearning #ArtificialIntelligence #MachineLearning #computervision #research #projects #thesis #Python

Learn the Cuckoo Search Algorithm in Hindi using Examples. Video Chapters: Cuckoo Search Algorithm (CSA) 00:00 Introduction 00:48 Topics Covered  01:16 Metaheuristic Optimization Algorithm Introduction 03:42 What is the Cuckoo Search Algorithm 05:38 CSA Rules 07:15 CSA Key Concepts 11:42 CSA Step-By-Step  24:24 Conclusion

Learn the Salp Swarm Algorithm step-by-step with examples. Video Chapters: Salp Swarm Algorithm (SSA)  00:00 Introduction 00:14 Topics Covered in this Video 00:53  Introduction to Salp Swarm Algorithm 03:56 SSA Working 05:17 SSA Mathematical Models 10:27 SSA Advantages  10:51 SSA Disadvantages 11:08 SSA Structure 11:38 SSA Applications 12:20 Real-Life Application using SSA 12:55 Optimizing Routing in Sensor Networks Using Salp Swarm Algorithm  18:15 Conclusion

Learn how to perform diversity analysis in metaheuristic algorithms step-by-step. Video Chapters:  Diversity Analysis in Metaheuristic Algorithms 00:00 Introduction 00:10 Methods to Balance Selection 03:08 Enhance Diversification in PSO and Prevent Premature Convergence 06:58 Diversity Maintaining Strategies in Optimization Algorithms 11:04 Diversity-Based Indicators  13:02 Conclusion

Learn how to do Diversity Analysis in Metaheuristic Algorithms. Video Chapters: Diversity Analysis 00:00 Introduction 01:00 What is Diversity? 02:18 Genotypic Diversity and Phenotypic Diversity Example 04:53 Diversity Analysis in Metaheuristic 08:57 How to Measure Diversity in Metaheuristic Algorithms? 09:40 How to Keep Diversity in Metaheuristic Algorithms? 11:11 Wind Turbine Layout Diversity Analysis 14:02 Low Diversity and High Diversity in Metaheuristic Algorithms 15:00 Diversity Analysis Techniques 17:30 Diversity Monitor and Control Techniques 18:40 Conclusion

Video Link Multi-Block Local Binary Pattern || Calculate LBP Corner Pixel Values ||  https://youtu.be/o8qfJWQ_FG0  Local Binary Patterns (LBP) is a simple and efficient technique used in image processing to describe the texture or patterns within an image. LBP is widely used for applications like face recognition and texture classification since it is easy to compute and very effective at capturing the texture in photos.  Step How LBP WORKS:  For each pixel in the image, LBP looks at the pixel’s neighbors, typically the 8 pixels surrounding it in a 3x3 grid. LBP compares each of these neighboring pixels with the center pixel. If the neighboring pixel has a value greater than or equal to the center pixel, it's marked as 1; otherwise, it's marked as 0. This comparison forms a binary number for the pixel.  The binary number is then converted into a decimal value. This value represents the texture pattern at that pixel. By doing this for every pixel in the image, LB...

Video Chapters: Algorithms Comparison 00:00 Introduction  00:18 Metaheuristic Algorithms 00:46 Why Comparision? 02:05 Algorithms Comparision 08:50 Comparision Table 12:14 Hybrid Algorithms 13:27 Conclusion

Learn how to calculate Pareto optimal solutions. Video Chapters: Pareto Optimality 00:00 Introduction 00:24 Pareto Optimality 02:33 Pareto Optimality Importance 03:29 Pareto Optimality Disadvantages 03:54 Pareto Optimality Applications 04:02 Example 1 Robot in Field 05:39 Steps to Calculate Pareto Optimality 07:41 Example 2 Math Example 11:03 Example 3 Resource Allocation Problem 16:09 Conclusion

Learn Multi-Objective Optimization:  PSO Example for Robots with Different Battery Levels Video Chapters: Robotics and PSO 00:00 Introduction 00:36 Robots Finding the Optimal Path 05:45 Multi-Objective Optimization 06:44 Objectives 08:46 Flowchart 09:08 Results 11:15 Conclusion

Learn Bat Algorithm Implementation in Python. Video Chapters: Bat Algorithm 00:00 Introduction 00:42 Bat Algorithm Key Concepts 01:58 Bat Algorithm Pseudocode 02:35 Objective Function 02:49 Parameters 03:09 Python Code 06:30 BA Main Loop Start 12:30 Result The Bat Algorithm is a nature-inspired optimization algorithm developed by Xin-She Yang in 2010. It is based on the echolocation behavior of bats. Bats use echolocation to detect prey, avoid obstacles, and navigate in the dark. The algorithm simulates this behavior to find optimal solutions in complex optimization problems. Applications: The Bat Algorithm has been used in various fields, including engineering design, image processing, data mining, and robotics, for solving complex optimization problems. PYTHON CODE: import numpy as np # Define the objective function  def objective_function(x):     return np.sum(x**2) # Initialize the bat population def initialize_bats(n_bats, dim, lower_bound, upper_bound, f_min, f_m...

Learn the role of deep learning in robotics. Video Chapters: Smart Robots 00:00 Introduction 00:42 Why Optimization? 03:47 Deep Learning  04:28 Role of Deep Learning in Robotics 07:03 How Deep Learning Applied in Robotics 09:58 Example Mobile Robot 14:33 Conclusion

Learn the role of Metaheuristics in Advanced Solutions in Marine Robotics. Video Chapters: Marine Robotics 00:00 Introduction 00:25 Marine Robots 02:11 Marine Robotics Applications   04:14 Marine Robotics Technologies 05:46 Marine Robotics Challenges 06:21 Marine Robotics Algorithms 10:30 Metaheuristic Algorithms in Marine Robotic 13:09 Conclusion 

Learn how to create an Objective Function for any real-life optimization problem. 00:00 Introduction 00:25 STEPS 02:41 Numerical Example 06:19 Objective Function Verification 07:48 Graphical Representation  08:31 Conclusion

Learn how to optimize hyperparameters using PSO. Video Chapters: Hyperparameter Optimization 00:00 Introduction 01:30 Problem 02:15 Hyperparameters 03:24 Problem Setup 04:15 Numerical Example Step-By-Step 12:00 Conclusion

Learn how to Optimize Hyperparameters in Deep Learning Using Particle Swarm Optimization (PSO) Video Chapters: Deep Learning + Particle Swarm Optimization 00:00 Introduction 00:59 Deep Learning 03:05 ANN Example 06:55 Deep Learning Applications 07:55 How to use Deep Learning 10:55 Deep Learning Tools 11:15 Hyperparameter Optimization Example 14:04 Hyperparameter 14:22 Conclusion 

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

Learn Artificial Intelligence and Metaheuristic Algorithm Real Life Applications Video Chapters: AI and Metaheuristics  00:00 Introduction 00:55 Metaheuristics 01:49 Artificial Intelligence 03:11 AI and Metaheuristics Collaboration 05:21 Robot Path Planning EXAMPLE 1 09:51 Route Optimization EXAMPLE 2 12:10 Outro

Learn Multi-Objective Particle Swarm Optimization Step-By-Step. Video Chapters: Multi-Objective PSO 00:00 Introduction 00:46 Multi-Objective Optimization 02:55 MOO Applications 04:00 Example 1 Multi-Objective Optimization Problem 07:26 Example 2 Multi-Objective Optimization Problem 08:25 Methods for Multi-Objective Optimization 09:50 Multi-Objective Particle Swarm Optimization 12:00 Example 3 Multi-Objective Optimization Problem 17:58 STEPS for Multi-Objective Particle Swarm Optimization 21:55 Conclusion 

Learn the Capuchin Search Algorithm Step-By-Step with Example 00:00 Introduction 01:04 About Capuchin 02:57 Leader 04:46 Capuchin Movements 05:42 Capuchin Strategies  07:37 Capuchin Search Algorithm Steps 23:55 Conclusion

Learn how to implement the Firefly Algorithm in Python. Video Chapters: FA in Python 00:00 Introduction 00:22 FA Steps 01:09 FA Using Python Code 14:48 Result

Learn Cuckoo Search via Levy Flights in Python Step-By-Step Video Chapters: CS in Python 00:00 Introduction 03:44 Objective Function 04:12 Population Initialization 05:58 Apply Cuckoo Search Algorithm 07:54 CS Main Loop Start  15:14 Result

Learn Prairie Dog Optimization (PDO) Algorithm Step-By-Step with Example Video Chapters: PDO Algorithm 00:00 Introduction 00:30 PDO Inspiration 01:19 PDO Benefits 02:07 About Prairie Dogs 03:34 PDO Process 04:15 PSO Mathematical Models 05:56 4 Time Periods in PDO 06:31 PDO Steps 13:43 Levy Distribution 17:43 Conclusion 18:09 Outro  

Learn Levy Flight Calculation using Numerical examples Step-By-Step. Video Chapters: Levy's Flight Calculation 00:00 Introduction 01:21 Levy Flight Equations 01:53 Levy Flight Applications 02:22 Step Length Equation 03:35 Numerical Example for Levy Flight Calculation 08:20 Conclusion  09:07 Outro

Learn the Cheetah Optimization Algorithm Step-By-Step with examples. Video Chapters: Cheeta Optimizer 00:00 Introduction 01:11 Topics Covered 02:00 About Cheetah  03:20 Cheetah Hunting Strategies 06:51 Cheeta Optimizer Step-By-Step 15:51 Mathematical Models 16:16 Search Mode 17:41 Attack Mode 18:36 Sit-And-Wait Mode 19:38 Outro

Learn Feature Selection Using Particle Swarm Optimization Step-By-Step. Video Chapters: FS using PSO 00:00 Introduction 00:24 Feature Selection Methods 01:11 Intelligent Feature Selection Techniques 02:46 Feature Selection Phases 03:34 Feature Selection using PSO 06:37 Mathematical Example 10:41 Conclusion Feature Selection using Any Metaheuristic 13:28 Outro

What is Fitness Value in Optimization Algorithms?  Video Chapters: Fitness Values in Optimization 00:00 Introduction 00:56 Algorithms Inspiration 03:05 Metaheuristic Algorithms 03:30 Metaheuristic Algorithms Steps 04:44 Calculate Fitness Values 07:45 Example 1 Find the Maxima of a Given Function using a Genetic Algorithm 11:09 Example 2 Find Maxima of Given Function using Genetic Algorithm 13:37 Outro

Learn What is Swarm Intelligence? Video Chapters: Swarm Intelligence 00:00 Introduction 01:01 Swarm Intelligence Features 01:42 Swarm Intelligence Algorithms 02:17 Swarm Intelligence Example 01 05:49 Swarm Intelligence Example 02 17:23 Swarm Intelligence Real Life Applications 08:37 Swarm Intelligence Example 03  11:03 Swarm Intelligence Advantages 12:26 Outro

Are you "Struggling with Research? Let's Make It Simple!" Video Chapters:  00:00 Introduction 00:57 Choose Research Area 01:57 Clarify Research Goals 03:58 Ask For Guidance from Mentor 04:37 Time Management 05:10 Learn Research Skills 06:09 Stay Organized 06:55 Learn New Concepts 07:09 Ask for Feedback 07:30 Maintain Ethical Standards 08:05 Review Existing Work 08:24 Define Research Objectives 08:41 Formulation 08:19 Data Collection 09:50 Analyze Results 10:06 Write Research Paper 10:23 Thesis Writing 10:37 Review Research Work 10:52 Presentation Time 11:16 Publish Your Research Work 11:27 Tools for Research Work  14:11 Outro

Learn how to use Levy Flights in Metaheuristic Algorithms Step-By-Step Video Chapters: LF in Optimization Algorithms 00:00 Introduction 00:38 Levy Flights Basic 01:32 How Levy Flights Work? 07:03 Levy Flights Step Size Calculation 08:51 Random Number Implementation using Levys Flight 10:10 Levy Flights In Metaheuristics 11:02 Apply Levy Flights in Metaheuristics 12:24 Levy Flights Based Algorithms 13:30 Levy Flight-Based Particle Swarm Optimization 13:39 Levy Flight-Based Cuckoo Search Algorithm 13:57 Levy Flight-Based Firefly Algorithm 14:18 Levy Flight-Based Bat Algorithm 14:31 Levy Flight-Based Flower Pollination Algorithm 15:17 Conclusion 15:54 Outro

  UGC NET 2020 Question Paper (PART 2)