The problem of how to manage uncertainties when modeling or designing an engineering structure is briefly addressed here. Uncertainties may be relevant in the case of real structures, due to intrinsic variability of mechanical and physical properties as well as to the lack of knowledge when information are scarce and/or subject to some errors, for instance related to the test procedure. It is s...

Clustering analysis is an effective method to discover and identify tumor classes. So, this paper proposes a Fuzzy C-Means clustering (FCM) algorithm based on Non-negative matrix factorization (NMF). Firstly, gene expression profiling (GEP) is simply processed through mean and variance of gene expression, which can then be mapped into a low dimensional space by NMF method. Finally, for discover...

Upper and lower conditional previsions are defined by the Choquet integral with respect to the Hausdorff outer and inner measures when the conditioning events have positive and finite Hausdorff outer or inner measures in their dimension; otherwise, when conditioning events have infinite or zero Hausdorff outer or inner measures in their dimension, they are defined by a 0-1 valued finitely, but ...

In this paper, we study continuity properties in Hausdorff topology for different special set multifunctions. Key–words: set multifunction, multi(sub)measure, regular, exhaustive, increasing/decreasing convergent, order continuity, probability.

Crowd analysis and abnormal trajectories detection are the hot topics in computer vision and pattern recognition. As more and more video monitoring equipments are installed in public places for public safety and public management, researches become urgent to learn the crowd behavior patterns through the trajectories obtained by the intelligent video surveillance technology. In this paper, the F...

To design a fuzzy rule-based classification system (fuzzy classifier) with good generalization ability in a high dimensional feature space has been an active research topic for a long time. As a powerful machine learning approach for pattern recognition problems, support vector machine (SVM) is known to have good generalization ability. More importantly, an SVM can work very well on a high (or ...

To design a fuzzy rule-based classification system (fuzzy classifier) with good generalization ability in a high dimensional feature space has been an active research topic for a long time. As a powerful machine learning approach for pattern recognition problems, support vector machine (SVM) is known to have good generalization ability. More importantly, an SVM can work very well on a high(or e...

This paper presents an implementation of visual learning by appearance in conjunction with an adaptive, nonlinear controller for fine-positioning a manipulator onto a grasping position. We use principal component analysis to reduce the dimension of raw camera images (about pixels) to lower-dimension vectors that can be used as inputs of our neuro-fuzzy controllers. It is shown that this approac...

In this paper, a new classification scheme of polarimetric synthetic aperture radar (PolSAR) images using fractal dimension as contextual information is proposed. Support vector machines (SVM) due to their ability to handle the nonlinear classifier problem are applied to a new fractal feature vector, which is constructed from Pauli decomposed vector and fractal dimensions. Fractal dimension is ...

In this paper, we first of all define the distance measure entitled generalized Hausdorff distance between two trapezoidal generalized fuzzy numbers (TGFNs) that has been introduced by Chen [10]. Then using a other distance and combining with generalized Hausdorff distance, we define the similarity measure. The basic properties of the above mentioned similarity measure are proved in detail. Fin...