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

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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 ...
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introduction to Merkle-Hellman knapsacks Algorithm

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 Ralph Merkle and Martin Hellman Developed the first algorithm for Public Key for public-key Encryption, called the knapsacks Algorithm.

This algorithm is based on the Knapsack Problem.[this is actually a simple problem]

Given a pile of Items, each with different weights, is it possible to put some of them in a bag (i.e., knapsack) in such a way that the knapsack has a certain weight?

If M1, M2, M3,.., Mn are given values and S is the Sum, Find out bi so that:

           S = b1M1 + b2M2 + ... + bnMn

Each bi can be 0 or 1.  [1 indicates the item is in the knapsack and 0 indicates that it is not].

A Block of Plain text equal in length to the number of items in the pile would select the items in the knapsack. The ciphertext is the resulting sum. 

For example: if the knapsack is 1, 7, 8, 12, 14, 20 then the plain text and the resulting Ciphertext is shown as: 



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

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