Interpoint squared distance as a measure of spatial clustering

The interpoint distance distribution as a descriptor of point patterns, with an application to spatial disease clustering.

The topic of this paper is the distribution of the distance between two points distributed independently in space. We illustrate the use of this interpoint distance distribution to describe the characteristics of a set of points within some fixed region. The properties of its sample version, and thus the inference about this function, are discussed both in the discrete and in the continuous set...

Revision of a fuzzy distance measure

Degree of Optimality as a Measure of Distance of Power System Operation from Optimal Operation

This paper presents an algorithm based on inter-solutions of having scheduled electricity generation resources and the fuzzy logic as a sublimation tool of outcomes obtained from the schedule inter-solutions. The goal of the algorithm is to bridge the conflicts between minimal cost and other aspects of generation. In the past, the optimal scheduling of electricity generation resources has been ...

Clustering by Maximizing Sum-of-Squared Separation Distance

Maximizing the separating margin is crucial for the good generalization performance of Support Vector Machines (SVMs). Analogous to the definition of separation distance or separating margin in SVMs, we propose a definition on separation distance in clustering tasks when a hyperplane is used to separate clusters. For given training data and a given metric distance, by maximizing the proposed se...

Clustering with a Domain-Specific Distance Measure

With a point matching distance measure which is invariant under translation, rotation and permutation, we learn 2-D point-set objects, by clustering noisy point-set images. Unlike traditional clustering methods which use distance measures that operate on feature vectors a representation common to most problem domains this object-based clustering technique employs a distance measure specific to ...