Comparison of Clustering Algorithms to Design New Clustering Approach

Using Metaheuristic Algorithms Combined with Clustering Approach to Solve a Sustainable Waste Collection Problem

Sustainability is a monumental issue that should be considered in designing a logistics system. In order to incorporate sustainability concepts in our study, a waste collection problem with economic, environmental, and social objective functions was addressed. The first objective function minimized overall costs of the system, including establishment of depots and treatment facilities. Addressi...

A new approach to clustering

-Estimation theory is used to derive a new approach to the clustering problem. The new method is a unification of centroid and mode estimation, achieved by considering the effect of spatial scale on the estimator. The result is a multiresolution method which spans a range of spatial scales, giving enhanced robustness both to noise in the data and to changes of scale in the data, by using compar...

A New Approach to Clustering

Clustering Rules: A Comparison of Partitioning and Hierarchical Clustering Algorithms

Previous research has resulted in a number of different algorithms for rule discovery. Two approaches discussed here, the ‘all-rules’ algorithm and multiobjective metaheuristics, both result in the production of a large number of partial classification rules, or ‘nuggets’, for describing different subsets of the records in the class of interest. This paper describes the application of a number ...

A Generalized Approach to Possibilistic Clustering Algorithms

Fuzzy clustering is an approach using the fuzzy set theory as a tool for data grouping, which has advantages over traditional clustering in many applications. Many fuzzy clustering algorithms have been developed in the literature including fuzzy c-means and possibilistic clustering algorithms, which are all objective-function based methods. Different from the existing fuzzy clustering approache...