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Subjects / keywords: Mathematics; Basis (linear algebra); Fuzzy set; Fuzzy logic; Artificial intelligence; Algebra over a field; Mathematical economics; Pure mathematics; Computer science; Geometry

Subjects / keywords: Mathematics; Possibility theory; Random variable; Fuzzy set; Probability distribution; Conditional probability; Fuzzy logic; Membership function; Variable (mathematics); Probability theory; Discrete mathematics; Probabil...

Subjects / keywords: Computer science; Fuzzy logic; Fuzzy set; Set (abstract data type); Operations research; Artificial intelligence; Mathematics; Programming language

Subjects / keywords: Fuzzy logic; Computer science; Fuzzy set; Artificial intelligence; Operations research; Mathematics

Subjects / keywords: Computer science

Subjects / keywords: Mathematics; Generalization; Fuzzy set; Modal; Set (abstract data type); Algebra over a field; Fuzzy set operations; Discrete mathematics; Fuzzy logic; Pure mathematics; Artificial intelligence; Computer science

Typologies are an important way of organizing the complex cause-effect relationships that are key building blocks of the strategy and organization literatures. Here, I develop a novel theoretical perspective on causal co...

When stakeholders are geographically distributed communication presents new challenges for software engineering community. In order to improve communication between stakeholders, we have previously proposed to apply lear...

Currently, Mathematical Morphology (MM) has become a powerful tool in Digital Image Processing (DIP). It allows processing images to enhance fuzzy areas, segment objects, detect edges and analyze structures. The techniqu...

By decision-making in a fuzzy environment is meant a decision process in which the goals and/or the constraints, but not necessarily the system under control, are fuzzy in nature. This means that the goals and/or the con...

Enrichment analysis is a popular method for analyzing gene sets generated by genome-wide experiments. Here we present a significant update to one of the tools in this domain called Enrichr. Enrichr currently contains a l...

The approach described in this paper represents a substantive departure from the conventional quantitative techniques of system analysis. It has three main distinguishing features: 1) use of so-called ``linguistic'' vari...

Professor Arnold Kaufmann did propose at least two types of indexes for estimating fuzziness in finite standard fuzzy sets. First one has an analogue formulation to that stated by Claude Shannon for measuring uncertainty...

This paper analyzes a fuzzy logic (FL) oriented instruction set (micro)controller and their implementations on FIPSOC1. VHDL code is synthesized using a small portion of FIPSOC FPGA2. This circuits are used from the mP80...

This paper introduces a fuzzy rule-based method for the recognition of hand gestures acquired from a data glove, with an application to the recognition of some sample hand gestures of LIBRAS, the Brazilian Sign Language....

There are three kinds of uncertainty in the process of fish-disease diagnosis, such as randomicity, fuzzy and imperfection, which affect the veracity of fish-disease diagnostic conclusion. So, it is important to construc...

The main advantage of a recurrent architecture is the ability to store information from prior system states. A recurrent fuzzy controller includes hidden fuzzy variables which makes the controller more appropriate to dea...

Abstract Two fuzzy versions of the k-means optimal, least squared error partitioning problem are formulated for finite subsets X of a general inner product space. In both cases, the extremizing solutions are shown to be ...

A fuzzy controller is usually designed by formulating the knowledge of a human expert into a set of linguistic variables and fuzzy rules. As it is well known, the use of prior knowledge can dramatically improve the perfo...

An application of Zadeh’s prototype theory in the Knowledge Acquisition process, is presented here, and as a practical example, to define a method for predicting the evolution of the forest fire occurrence-danger rate ...

A fuzzy controller is usually designed by formulating the knowledge of a human expert into a set of linguistic variables and fuzzy rules. As it is well known, the use of prior knowledge can dramatically improve the perfo...

Robot arm control is a difficult problem. Fuzzy controllers have been applied succesfully to this control task. However, the definition of the rule base and the membership functions is itself a big problem. In this paper...

In our opinion, approximate reasoning is one of the most fascinating branches of I.A., and it has generated an extensive literature. One of the goals of approximate reasoning models is to cope with inference patterns mor...

Clustering techniques can be used as a basis for classification systems in which clusters can be classified into two categories: positive and negative. Given a new instance enew, the classification algorithm is applied t...