A Review on Swarm Intelligence Algorithms Applied for Data Clustering

2021 ◽  
pp. 429-440
Author(s):  
N. Yashaswini Gowda ◽  
B. R. Lakshmikantha
Keyword(s):  
Swarm Intelligence ◽  
Data Clustering

scholarly journals A General Framework for Mixed and Incomplete Data Clustering Based on Swarm Intelligence Algorithms

Mathematics ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 786
Author(s):  
Yenny Villuendas-Rey ◽  
Eley Barroso-Cubas ◽  
Oscar Camacho-Nieto ◽  
Cornelio Yáñez-Márquez
Keyword(s):  
Swarm Intelligence ◽  
Data Clustering ◽  
Incomplete Data ◽  
Missing Values ◽  
Clustering Algorithms ◽  
Bat Algorithm ◽  
Hybrid Features ◽  
Bee Colony ◽  
Learning Tasks ◽  
Clustering Data

Swarm intelligence has appeared as an active field for solving numerous machine-learning tasks. In this paper, we address the problem of clustering data with missing values, where the patterns are described by mixed (or hybrid) features. We introduce a generic modification to three swarm intelligence algorithms (Artificial Bee Colony, Firefly Algorithm, and Novel Bat Algorithm). We experimentally obtain the adequate values of the parameters for these three modified algorithms, with the purpose of applying them in the clustering task. We also provide an unbiased comparison among several metaheuristics based clustering algorithms, concluding that the clusters obtained by our proposals are highly representative of the “natural structure” of data.

Swarm intelligence based algorithms for data clustering

2011 ◽  
Author(s):  
Jinfeng Ding ◽  
Jingbo Shao ◽  
Yuyan Huang ◽  
Linyang Sheng ◽  
Wei Fu ◽  
...  
Keyword(s):  
Swarm Intelligence ◽  
Data Clustering

Swarm Intelligence in Solving Bio-Inspired Computing Problems

2016 ◽  
pp. 87-110
Author(s):  
Debi Prasanna Acharjya ◽  
Ahmed P. Kauser
Keyword(s):  
Swarm Intelligence ◽  
Data Clustering ◽  
Real Life ◽  
Biological Data ◽  
Behavioral Models ◽  
Biologically Inspired ◽  
Generative Power ◽  
Life Problems ◽  
Intelligence Technique

Currently, a huge amount of data is available across various domains including biological data. Classification of these data, clustering, and data analysis is tedious and has become popular in recent research. In particular, bio-inspired computing is the field that mends together mathematics, computer science, and biology to develop tools to store, scrutinize, and interpret the biological data. It is also used to solve real life problems like sequencing biological data, data clustering, and optimization. Swarm intelligence is an emerging field of biologically inspired artificial intelligence technique that is based on the behavioral models of social insects. This chapter provides an overview of swarm intelligence algorithms in solving bio-inspired computing problems. It is an attempt to explore the working nature, applications, and generative power of various bio-inspired computing algorithms. The main intent is to furnish a comprehensive study of swarm intelligence algorithms in the literature so as to inspire further research in the area of biologically inspired computing.

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