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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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Metaheuristic Optimization Algorithms in Web Mining, Text Clustering, Bi...

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Metaheuristic Optimization Algorithms in Big Data, Web Mining and Text Clustering.


Metaheuristic optimization algorithms are best swarm intelligence methods and widely used today in Big Data, Web Mining AND Text clustering. Using metaheuristic optimization algorithms we can solve complex Machine Learning problems. 

Clustering: Clustering is a common text mining technique. We can used clustering technique for the representation of Dataset that contain similarities between objects. We can use clustering in Web mining, Image Processing, Sentiment Analysis, Data Clustering, Text document clustering, and Text classification. Clustering technique is classified into 3 classes:
1.) Overlapping
2.) Partitioning
3.) Hierarchical 

In Partitioning Process we can use metaheuristic optimization approaches. Partitioning process is used for the transformation of any given problem into optimization problem. Partitioning process is based on either minimization or maximization. Partitioning methods are applied in:
- Computer Science for Web mining, Image processing and Image Pattern Recognition.
- In robotics
- In wireless sensor network

Metaheuristic Approaches can be used to solve big data and clustering problems:
- Swarm based optimization algorithms
- Evolutionary Algorithms
- Physics based optimization Algorithms
- Art based optimization algorithms
- Bio-inspired optimization algorithms


This video is based on role of Metaheuristic Optimization Algorithm on the Text Clustering applications, Big Data and Web Mining. and text clustering.
Video Timestamps:
Introduction: 00:00
Metaheuristic Optimization Algorithms Role: 00:25
Text Clustering: 01:12
Clustering Techniques: 02:20
Fitness Function: 02:32
Partitioning Methods: 03:02
Clustering Example: 04:04
Clustering Process: 05:06
Text Clustering Problem: 06:54
Metaheuristic Optimization Algorithms in Text Clustering: 07:46
Text clustering measures: 09:19
Web Document Clustering: 09:30


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