New Post

Life Skills for Everyday Success ~xRay Pixy

Image
Life skills are the basic abilities we need to handle daily challenges and live a healthy, balanced life. They help us think clearly, manage our feelings, make good decisions, solve problems, and build good relationships with others. The World Health Organization (WHO) highlights 10 important life skills: 1.) Thinking skills: decision-making, problem-solving, creative thinking, critical thinking 2.) Social skills: communication, empathy, interpersonal skills 3.) Emotional skills: self-awareness, coping with emotions, coping with stress Life skills are the tools that make us stronger, wiser, and calmer in real life — at home, in school, at work, and in the community :) Life Skills for Everyday Success ~xRay Pixy https://youtu.be/AMsUfKRl4kw Video Chapters: Life Skills 00:00 Introduction 01:07 Life Skills 09:42 Real Life Challenge 13:44 Task For You #LifeSkills #SuccessTools #StressFreeLiving #algorithm #optimization #research #happylearning #algorithms #meta #optimizationtechniques #swa...

All Members-Based Optimizer (AMBO) || STEP-BY-STEP || ~xRay Pixy

All Members-Based Optimizer (AMBO)


Learn All Members-Based Optimizer Step-by-Step with Examples.
Algorithm Type: Metaheuristic Optimization Technique
Algorithm Main Idea: Make more use of the Population Matrix.
Tested on Different Benchmark Test Functions.
Algorithm Performance: Provide Better results in comparison with different metaheuristic optimization algorithms.
Used for Solving Optimization Problems.

ALGORITHM MAIN IDEA

Make use of the Population Matrix and All Members can play role in Updating Algorithm Population.

ALL MEMBERS-BASED OPTIMIZER STEPS

STEP 01: Initialize Algorithm Important Parameters. STEP 02: Initialize Population Randomly in the Search Space. STEP 03: Evaluate Initial Population using the Fitness Function. STEP 04: Check While (Current Iteration < Maximum Iteration) Do STEP 05: Update Members Position and Best Member Position. STEP 06: Update Population Members using STAGE 01. STEP 07: Update Population Members using STAGE 02. STEP 08: Save Best Solution in the Memory. STEP 09: Increment Counter. STEP 10: Best Solution Found.

ALL MEMBERS-BASED OPTIMIZER FLOWCHART



Comments

Popular Post

PARTICLE SWARM OPTIMIZATION ALGORITHM NUMERICAL EXAMPLE

Cuckoo Search Algorithm for Optimization Problems

Particle Swarm Optimization (PSO)

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

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

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

Grey Wolf Optimization Algorithm

Grey Wolf Optimization Algorithm Numerical Example

Bat algorithm Explanation Step by Step with example

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