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Cat Swarm Optimization Algorithm | CSO Algorithm |  Cat Swarm Optimization Algorithm  Video Chapters: CSO Introduction: 00:00 Cat Swarm Optimization Sub-Models 02:03 CSO Seeking Mode: 03:26 CSO Tracing Mode: 05:19 Cat Swarm Optimization flow chart: 06:56 Cat Swarm Optimization Steps: 08:25 Cat's: 10:48 Cat Swarm Optimization Algorithm is an Metaheuristic Optimization Algorithm. It comes in the category of Nature Inspired Swarm Based Optimization Algorithm. As we all know Nature Inspired Swarm Based Optimization Algorithms are Stochastic methods designed to solve different optimization problem's. Cat Swarm Optimization Algorithm is inspired by behavior of cats in real life. Cat Swarm Optimization Algorithm is invested in 2006 by Shu Chuan Chu. Author tested Cat Swarm Optimization Algorithm using 23 Classical benchmark functions and 10 modern benchmark function.  Two sub-models are used in Cat Swarm Optimization Algorithm to describe cat's behavior. They are modeled on Cats b

  Neuro-fuzzy hybrid system tutorial |Soft Computing| Neuro-Fuzzy Hybrid System (NFHS) - Soft Computing (Neural Network) An introduction to the Neuro-Fuzzy System. In the field of artificial intelligence, neuro-fuzzy refers to combinations of artificial neural networks and fuzzy logic. Neuro-Fuzzy Hybrid System is a combination of Neural Network and Fuzzy Logic. Neuro-fuzzy hybridization results in a hybrid intelligent system that synergizes these two techniques by combining the human-like reasoning style of fuzzy systems with the learning and connectionist structure of neural networks. Neuro-fuzzy hybridization is widely termed as the fuzzy neural network (FNN) or neuro-fuzzy system (NFS) in the literature. Neuro-fuzzy system (the more popular term is used henceforth) incorporates the human-like reasoning style of fuzzy systems through the use of fuzzy sets and a linguistic model consisting of a set of IF-THEN fuzzy rules. The main strength of neuro-fuzzy systems is that they are uni

Ant Colony Optimization Metaheuristics for the Traveling Salesman Problem Numerical Example In this video you will learn, How to Solve Traveling Salesman Problem (TSP) using Ant Colony Optimization Algorithm (ACO). Ant System for the Traveling Salesman Problem Chapters: Introduction : 00:00 Traveling Salesman Problem (TSP): 00:33 Ant Colony Optimization Traveling Salesman Problem Example: 02:11 Distance Calculation between Cities: 04:30 Solution Construction for Artificial Ants: 06:45 Ants Tour Comparison for TSP: 14:52 Conclusion: 15:45 Part 1: Learn Ant Colony Optimization Algorithm Ant Colony Optimization Algorithm step-by-step with Example (ACO) ~xRay Pixy https://youtu.be/qYXeMFCf1Gk Ant System for the Traveling Salesman Problem. Ant Colony Optimization is a Nature Inspired Approach. Ant Colony Optimization (ACO) algorithm is basically inspired by the foraging behavior of ants searching for suitable paths between their colonies and food source. Ant Colony O

WHAT IS ALGORITHM DESIGN? Algorithm Design is a specific method to create mathematical process in solving various classical problems, real world complex problems. Techniques for designing and implementing algorithm design are design patterns. ALGORITHM DESIGN TECHNIQUES We have 5 base techniques that can be used to design any algorithm.  Divide and Conquer Greedy Method Dynamic Programming Back Tracking Branch and Bound WHAT IS DIVIDE AND CONQUER TECHNIQUE?  In branch and bound technique, we break the main problem into several sub-problems. Sub-problems are similar to original problem but smaller in size. To solve given problem algorithm call themselves to deal with subproblems. Once subproblems are solved recursively then combine these solutions to create a final solution for the original problem. Merge Sort Algorithm follow Divide and Conquer method. Step 01: Divide the main problem into subproblems [n/2]. Step 02: Solve the subproblems recursively.  Step 03: Combine the solutions to