In this paper, the collocation method is considered to solve nonhomogeneous for fourth order fuzzy boundary value problems, which fuzziness appeared together in conditions and term of differential equation. The solution depends on transforming problem equivalent crisp problems using concept α-level sets.

As a natural generalization of a measure space, Butnariu and Klement introduced T-tribes of fuzzy sets with T-measures. They gave a complete characterization of T-measures for a Frank triangular norm T. Here we characterize T-measures with respect to non-Frank strict triangular norms. We show the speciic roles of Frank triangular norms and a newly introduced family, nearly Frank triangular norm...

We extend the shape signature based on the distance of the boundary points from the shape centroid, to the case of fuzzy sets. The analysis of the transition from crisp to fuzzy shape descriptor is first given in the continuous case. This is followed by a study of the specific issues induced by the discrete representation of the objects in a computer. We analyze two methods for calculating the ...

By extending the Bonferroni mean operator to the intuitionistic fuzzy situation, we introduce a new kind of aggregating operator: the induced generalized weighted Bonferroni mean(I-GWBM) operator. The I-GWBM operator includes many famous aggregation operators for intuitionistic fuzzy sets(IFSs) as special cases. Then, we generalize the I-GWBM operator by using quasi-arithmetic means and propose...

In the paper, we proposed a model called Adaptive Threshold Level Set Without Edge that is applied on the segmentation of GM in brain MR images. Threshold to find the boundary of GM is automatically obtained by fuzzy c mean algorithm. A similarity index (SI) is used for quantitative evaluation of the segmentation results. By testing 134 planar MR brain images and comparing to the gold standard ...

Soft Computing is an emerging field that consists of complementary elements of fuzzy logic, neural computing and evolutionary computation. Soft computing techniques have found wide applications. One of the most important applications is edge detection for image segmentation. The process of partitioning a digital image into multiple regions or sets of pixels is called image segmentation. Edge is...

Many image segmentation techniques have been developed over the past two decades for segmenting the images, which help for object recognition, occlusion boundary estimation within motion or stereo systems, image compression, image editing. In this, there is a combined approach for segmenting the image. By using histogram equalization to the input image, from which it gives contrast enhancement ...

Current intrusion detection techniques mainly focus on discovering abnormal system events in computer networks and distributed communication systems. Clustering techniques are normally utilized to determine a possible attack. Due to the uncertainty nature of intrusions, fuzzy sets play an important role in recognizing dangerous events and reducing false alarms level. This paper proposes a dynam...

In this paper an optimized method for unsupervised image clustering is proposed. Generally a Novel Fuzzy C Means (FCM) or FCM based clustering algorithm are used for clustering based image segmentation but these algorithms have a disadvantage of depending upon supervised user inputs such as number of clusters. Our proposed algorithm enhances an unsupervised preliminary process known as Double C...

Zoning is widely used for obtaining topological features of handwritten characters. In this paper we have modified the zoning criteria using fuzzy boundary of individual zones keeping the point in mind that writing style of different persons may shift the structural pattern of the character from one zone to the adjacent zone. The zone-wise normalized distance of individual black pixel along wit...