In this paper we present a new approach to measuring similarity between two shape of object. In conventional method, centroid contour distance (CCD) is formed by measuring distance between centroid (center) and boundary of object, but this method cannot capture if an object have multiple boundary in the same angle. We develop a novel approach feature shape by measuring distance between centroid...

Traffic congestion is a major concern for many cities throughout the world. In a general traffic light controller, the traffic lights change at a constant cycle time. Hence it does not provide an optimal solution.Many traffic light controllers in current use are based on the “time-of-the-day” scheme, which use a limited number of predetermined traffic light patterns and implement these patterns...

They appear often situations in a system’s operation characterized by a degree of vagueness and/or uncertainty. In the present paper we use principles of fuzzy logic to develop a general model representing such kind of situations. We also present 3 alternative methods for measuring a fuzzy system’s effectiveness. These methods include the measurement of the system’s total possibilistic uncertai...

Glaucoma is a disease which affects the eye and causes blindness. It is an ophthalmologist disease characterized by an increase in Intraocular Pressure (IOP). The glaucoma usually affects the optic disc on the retina which increases the cup size. There are various parameters to identify and diagnose glaucoma. The clustering technique is introduced to detect the glaucoma from the optic disc and ...

<span lang="EN-US">Due to various killing diseases in the world, medical data clustering is a very challenging and critical task handle take proper decision from multidimensional complex an effective manner. The most familiar suitable speedy algorithm K-means than other traditional approaches. But extra sensitive for initialization of centroid it can easily surround. Thus, there necessity...

This paper presents some theoretical considerations about the variance of a fuzzy set and introduces covering–based algorithm for computing bounds an interval Type–2 set. The proposed obtains all possible variances unlike other algorithms which are based on center centroid to obtain relative is proven be always bigger than absolute variance. A comparison given through different examples where s...

Clustering of web user sessions is extremely significant to comprehend their surfing activities on the internet. Users with similar browsing behaviour are grouped together, and further analysis of discovered user groups by domain experts may generate usable and actionable knowledge. In this paper, a conglomerative clustering approach is presented to identify web user session clusters from web s...

This chapter describes different methods for comparing and ordering fuzzy numbers. Theoretically, fuzzy numbers can only be partially ordered, and hence cannot be compared. However, in practical applications, such as decision making, scheduling, market analysis or optimisation with fuzzy uncertainties, the comparison of fuzzy numbers becomes crucial. Theoretically, fuzzy numbers can only be par...

The fuzzy c-means algorithm is a soft version of the popular k-means clustering. As is well known, the k-means method begins with an initial set of randomly selected exemplars and iteratively refines this set so as to decrease the sum of squared errors. The k-centers clustering is moderately sensitive to the initial selection of centers, so it is usually rerun many times with different initiali...