New Post

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

Image
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 ā€“ Based on the reproductive mechanisms of poplar trees. Two Key Processes : Sexual Propagation (Seed Dispersal) ā€“ Uses wind to spread seeds, allowing broad exploration. Asexual Reproduction (Cuttings) ā€“ Strong branches grow ...

Transient Search Optimization Algorithm || Step-By-Step || ~xRay Pixy



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 doesnā€™t immediately settle into its final, stable state. Instead, it goes through a transient phase where:

  • Inductors resist sudden changes in current.
  • Capacitors resist sudden changes in voltage.

This creates oscillations or fluctuations in the system before the circuit stabilizes at its steady state. This behavior is governed by second-order differential equations.

Key Elements of Transient Behavior

  1. Energy Storage Elements:

    • Inductors (L) store energy in magnetic fields.
    • Capacitors (C) store energy in electric fields.
  2. Transient Response:

    • During the transient phase, the circuit's behavior is dynamic and fluctuates due to the energy exchange between L and C.
  3. Steady-State Response:

    • After the transient response fades, the circuit settles into a stable output (steady state).
  4. Damping:

    • The rate at which the oscillations reduce depends on the damping coefficient (Ī±). If damping is low, the system oscillates longer before stabilizing.


#optimization #algorithm #metaheuristic #robotics #deeplearning #ArtificialIntelligence #MachineLearning #computervision #research #projects #thesis #Python
#optimizationproblem #optimizationalgorithms 

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

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

Grey Wolf Optimization Algorithm

Grey Wolf Optimization Algorithm Numerical Example

Bat algorithm Explanation Step by Step with example