In this paper we propose a fuzzy goal programming method for obtaining a satisfactory solution to a bi-level multi-objective absolutevalue fractional programming (BLMO-A-FP) problems. In the proposed approach, the membership functions for the defined fuzzy goals of all objective functions at the two levels as well as the membership functions for vector of fuzzy goals of the decision variables c...

Discriminant analysis is a classification method that can predict the group membership of a newly sampled observation. In discriminant analysis, classification of new observed data has an uncertainty. In this paper, the confidence degree is introduced to determine the confidence of classification of new observed data. Then, a Monte Carlo-based sensitivity analysis is applied to an assessment of...

Fuzzy sets are relatively new to social science. The first comprehensive introduction of fuzzy sets to the social sciences was offered by Michael Smithson (1987). However, applications were few and far between until the basic principles of fuzzy set analysis were elaborated through Qualitative Comparative Analysis (QCA; see Ragin 1987; 2000), an analytic system that is fundamentally settheoreti...

The main aim of this paper is to connect R-Fuzzy sets and type-2 fuzzy sets, so as to provide a practical means to express complex uncertainty without the associated difficulty of a type-2 fuzzy set. The paper puts forward a significance measure, to provide a means for understanding the importance of the membership values contained within an R-fuzzy set. The pairing of an R-fuzzy set and the si...

We present a pseudo-observed variable based regularization technique for latent variable mixed-membership models that provides a mechanism to impose preferences on the characteristics of aggregate functions of latent and observed variables. The regularization framework is used to regularize topic models, which are latent variable mixed membership models for language modeling. In many domains, d...

We propose a fuzzy logic recursive scheme for motion detection and spatiotemporal filtering that can deal with the Gaussian noise and unsteady illumination conditions in both the temporal and spatial directions. Our focus is on applications concerning tracking and denoising of image sequences. We process an input noisy sequence with fuzzy logic motion detection to determine the degree of motion...

We study the complexity of the following problems in the streaming model. Membership testing for DLIN. We show that every language in DLIN can be recognised by a randomized one-passO(log n) space algorithm with inverse polynomial one-sided error, and by a deterministic p-pass O(n/p) space algorithm. We show that these algorithms are optimal. Membership testing for LL(k). For languages generated...

This paper presents a fuzzy goal programming (FGP) procedure for solving multilevel programming problems (MLPPs) having chance constraints in large hierarchical decision organizations. In the proposed approach, first the chance constraints of a problem are converted into their respective deterministic equivalent in the decision making context. Then, the objective functions of decision makers (D...

The roughness of a rough set arises from the existence of its boundary region. In such a boundary region, each object has a non-zero rough membership degree. When an object’s rough membership degree is regarded as its fuzzy membership degree, a rough set can induce a fuzzy set. This relationship motivates us to assert that there may exist some inherent relations between the roughness of a rough...