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

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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 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 (α). If damping is low, the system oscillates longer before stabilizing.


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

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