Fuzzy Ants with Cluster Mining

Lingaraj. N. Desai; K. Krishnamoorthy

Ant-based techniques are designed to take biological inspirations on the behavior of these social insects. Data clustering techniques are classification algorithms that have a wide range of applications, from Biology to Image processing and Data presentation. Since real life ants do perform clustering and sorting of objects among their many activities, we expect that a study of ant colonies can provide new insights for clustering techniques. The aim of clustering is to separate a set of data points into self-similar groups such that the points that belong to the same group are more similar than the points belonging to different groups. Each group is called a cluster. Data may be clustered using an iterative version of the Fuzzy C means (FCM) algorithm, but the draw back of FCM algorithm is that it is very sensitive to cluster center initialization because the search is based on the hill climbing heuristic...

Select Volume / Issues:

• Volume 7,Issue 6, Nov. 2016

Year:

2016

Type of Publication:

Article

Keywords:

Ant Optimization; Cluster; Mining; Fuzzy

Journal:

IJECCE

Volume:

7

Number:

6

Pages:

331-334

Month:

November

ISSN:

2249-071X