In the paper a model to predict the concentrations of particulate matter PM10, PM2.5, SO2, NO, CO and O3 for a chosen number of hours forward is proposed. The method requires historical data for a large number of points in time, particularly weather forecast data, actual weather data and pollution data. The idea is that by matching forecast data with similar forecast data in the historical data...

Paraconsistent intuitionistic fuzzy set is an extension of intuitionistic fuzzy set or interval-valued fuzzy set. It relaxes the requirement that t + f ≤ 1, where t is grade of truth-membership and f is grade of false-membership. In paraconsistent intuitionistic fuzzy set, t, f ∈ [0, 1], 0 ≤ t + f ≤ 2. In this paper, we present a generalization of the relational model of data based on paraconsi...

We employ mixed-membership (or grade-of-membership) techniques—of growing popularity in medical diagnostics, psychology, genetics, and machine learning—in order to identify prototypical profiles of survey respondents based on their answers to questions aimed at uncovering their basic orientations or ideological predispositions. In contrast with factor analytic techniques and IRT approaches, we ...

Present analytical functions and conventional cartographic modeling techniques in Geographic Information Systems (GIS) are based on Boolean logic, which implicitly assumes that objects in a spadal database and their attributes can be uniquely defined. The inherent constraint of the classical set theory does not allow for partial set membership conditions and imprecise information in GIS. The in...

The backing of the fuzzy ideal is normal ideal in some ring and in same time there fuzzy set whose is not fuzzy ideal and it backing set is ideal, i.e., it crisp is normal ideal. Consequently, in this paper we constructing a fuzziness function which defined on fuzzy sets and assigns membership grade for every fuzzy set whose it backing set are crisp ideal. Now, Let  be collection of all fuzzy s...

By analyzing related issues in psychology and linguistics, two basic types of fuzziness can be attributed to similarity and relativity, respectively. In both cases, it is possible to interpret grade of membership as the proportion of positive evidence, so as to treat fuzziness and randomness uniformly.

[This corrects the article DOI: 10.1371/journal.pgen.1006599.].

This paper focuses on model interpretation issues and employs a geometric approach to compare the potential value of using the Grade of Membership (GoM) model in representing population heterogeneity. We consider population heterogeneity manifolds generated by letting subject specific parameters vary over their natural range, while keeping other population parameters fixed, in the marginal spac...