New Post

Avascular Necrosis (AVN) || Early Detection, Better Outcomes || ~xRay Pixy

Image
Avascular Necrosis (AVN) is a condition where blood flow to the bone is reduced, causing bone cells to die. This leads to pain, joint damage, and difficulty in movement, especially in the hip. Early diagnosis and proper treatment can prevent permanent bone damage and improve quality of life. Video Chapter: AVN 00:00 Introduction 00:45 What is AVN? 01:55 About Bone Tissue 02:49 AVN Causes 03:38 AVN Symptoms 04:11 AVN Diagnosis 04:56 AVN of femoral head 05:33 How AVN Develops 07:28 Conclusions #optimization #algorithm #metaheuristic #robotics #deeplearning #ArtificialIntelligence #MachineLearning #computervision #research #projects #thesis #Python #optimizationproblem #optimizationalgorithms 

Hybrid Grasshopper Optimization Algorithm with Genetic Algorithm

Hybrid Grasshopper Optimization Algorithm and Genetic Algorithm


GOA-GA Hybrid Metaheuristics Video Chapters: Introduction: 00:00 Hybrid Metaheuristics: 01:11 Metaheuristic Hybridization Types: 02:47 Hybrid Grasshopper Optimization Algorithm - Genetic Algorithm: 04:06 Hybrid Grasshopper and Genetic Algorithm Steps: 08:54 Conclusion: 13:00

Hybrid methods are powerful as compared to others. Suppose, we have 2 Algorithms: Algorithm A and Algorithm B. Now suppose we merge the merits of both algorithms and formed Hybrid A-B Algorithm. New Algorithm i.e., Hybrid A-B Algorithm is better as compared to Algorithm A or Algorithm B.

Metaheuristics Hybridization Types:
  • Metaheuristic with Metaheuristic.
  • Metaheuristic with Exact Methods.
  • Metaheuristic with Constraint Programming, Artificial Intelligence.
  • Metaheuristic with Data Mining and Machine Learning Techniques.
Hybrid Grasshopper Optimization Algorithm and Genetic Algorithm |Hybrid G.O.A - G.A.|
  1. Hybrid GOA-GA is a combination of 2 Meta-heuristics.
  2. Author Combined the merits of the Grasshopper Optimization Algorithm and Genetic Algorithm and created Hybrid Grasshopper Optimization Algorithm with Genetic Algorithm to solve the system of non-linear equations.
  3. Metaheuristic Algorithm Challenges: Large Search Space, Variables, Parameters, Algorithm trapped into local optima, High Computation Cost. Hybrid Meta-heuristics are used to overcome such problems.
  4. In Hybrid GOA-GA , Genetic algorithm is used to prevent the algorithm to trapped in local optima. And Grasshopper algorithm is used for the Global search.
  5. Grasshopper algorithm is used for Exploration Phase (i.e., Global Search) and the Genetic Algorithm is used for the Exploitation phase (i.e., Local Search).



Comments

Popular Post

PARTICLE SWARM OPTIMIZATION ALGORITHM NUMERICAL EXAMPLE

Cuckoo Search Algorithm for Optimization Problems

PSO (Particle Swarm Optimization) Example Step-by-Step

Particle Swarm Optimization (PSO)

PSO Python Code || Particle Swarm Optimization in Python || ~xRay Pixy

how is the LBP |Local Binary Pattern| values calculated? Step-by-Step with Example

Whale Optimization Algorithm Code Implementation || WOA CODE || ~xRay Pixy

Grey Wolf Optimization Algorithm

Grey Wolf Optimization Algorithm Numerical Example

GWO Python Code || Grey Wolf Optimizer in Python || ~xRay Pixy