This study presented a method of real-time traffic condition identification based on the fuzzy c-means clustering and travel time prediction on urban expressway. The traffic flow characteristics of expressway were analyzed and the traffic flow states were divided into four classes. Then the fuzzy c-means clustering technique was used to classify the sampled historical data and the clustering ce...

Clustering is a somewhat confusing topic theoretically. In large part this is because there are many different kinds of clustering problems. In addition, the true goals in clustering are often difficult to measure, making the task seem not well-defined and under-specified. In this note we discuss one approach from [6] to theoretically formulating a certain broad class of clustering problems, an...

Article history: Received 9 August 2015 Accepted 22 September 2015 Submitted by R. Brualdi MSC: 05C50 05C75 05C82

Computer usage in musicology seems to be developing somewhat more slowly than in other research areas in the humanities. Many papers in the field limit themselves to discussing musical databases, and elementary types of statistical analyses, involving note or interval counts. With some exceptions (for example, Morando, 1979 and Steinbeck, 1976) there is little mention of the powerful statistica...

In this paper we develop a method for clustering all types of belief functions, in particular nonconsonant belief functions. Such clustering is done when the belief functions concern multiple events, and all belief functions are mixed up. Clustering is performed by decomposing all belief functions into simple support and inverse simple support functions that are clustered based on their pairwis...

We analyze criminal careers through crime nature, frequency, duration and severity. We propose a tool that yields a visual clustering of these criminal careers, enabling the identification of classes of criminals.