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Markov Chains || Step-By-Step || ~xRay Pixy

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Learn Markov Chains step-by-step using real-life examples. Video Chapters: Markov Chains 00:00 Introduction 00:19 Topics Covered 01:49 Markov Chains Applications 02:04 Markov Property 03:18 Example 1 03:54 States, State Space, Transition Probabilities 06:17 Transition Matrix 08:17 Example 02 09:17 Example 03 10:26 Example 04 12:25 Example 05 14:16 Example 06 16:49 Example 07 18:11 Example 08 24:56 Conclusion
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Crow Search Algorithm (CSA) / Crow Search Optimization (CSO) Algorithm

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What is the Crow search algorithm?

Crow search algorithm (CSA) is a population-based algorithm. Crow search algorithm is similar to Particle Swarm Optimization (PSO) algorithm. Crow search algorithm mimics the crow's intellegent behavior. CSA is based on crow's intelligent behavior. 

Key Point About Crow's

Crows live in large families and care for younger ones. They eat insects, worms, nuts, fruits, food, birds, non-insects, etc. They can hide excess food in hiding places and retrieve it when needed. Age: 14-17 years.

Crow can memorize the hiding place positions.

They follow each other to steal their food.

Crows protect their hiding places from attackers.

Two main parameters used in the CSA algorithm:

Flights Length,

Awareness Probability. 

Crow Search Optimization Algorithm Main Concepts 

Crow store excess food in hiding places and retrieve it when needed. 

Crow cheat each other (i.e., they steal each other food).


Crow Search Algorithm Step-by-Step with Example ~xRay Pixy

Crow search algorithm Video Link : Crow search algorithm

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

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

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