In the framework of noncommutative geometry we describe spinor fields with nonvanishing winding number on a truncated (fuzzy) sphere. The corresponding field theory actions conserve all basic symmetries of the standard commutative version (space isometries and global chiral symmetry), but due to the noncommutativity of the space the fields are regularized and they contain only finite number of ...

The prevalence of smart devices and the wireless Internet environment have enabled users to exploit environmental sensor data in a variety of fields. This has engendered various research issues in the development of context-awareness technology. In this paper, we propose a novel method where semantic web technology and the fuzzy concept are used to perform tasks that express and infer the user’...

In this paper, we firstly defined neutrosophic parameterized neutrosophic soft sets(npn−soft sets) which is combination of a neutrosophic sets and a soft sets. Our npn−soft sets generalizes the concept of the other soft sets such as; fuzzy soft sets, intuitionistic fuzzy soft sets, neutrosophic soft sets, fuzzy parameterized soft sets, intuitionistic fuzzy parameterized soft sets, neutrosophic ...

We give a framework to describe gauge theory on a certain class of commutative but nonassociative fuzzy spaces. Our description is in terms of an Abelian gauge connection valued in the algebra of functions on the cotangent bundle of the fuzzy space. The structure of such a gauge theory has many formal similarities with that of Yang-Mills theory. The components of the gauge connection are functi...

Pattern classification is one of the most important topics for machine learning research fields. However incomplete data appear frequently in real world problems and also show low learning rate in classification models. There have been many researches for handling such incomplete data, but most of the researches are focusing on training stages. In this paper, we proposed two classification meth...

In this paper modifications of intensifiers have been done for the injection into the receptive field of the fuzzy neural networks. Algorithmic developments for these modifiers are carried out for single-input single-output (SISO) as well as for multi-input multi-output (MIMO) fuzzy neural networks. This work can be beneficial for applications in different fields such as image processing, patte...

To demonstrate the applicability and feasibility of AI technology in nuclear fields in China, a fuzzy controller to control the reactor power of China Advanced Research Reactor (CARR) is designed in this paper. The fuzzy controller uses Mamdani inference system based 2 inputs-power difference and power period, 1 outputvelocity of control rods. To evaluate the performance of the fuzzy controller...

Rough set theory provides a methodology for data analysis based on the approximation of concepts in information systems. It revolves around the notion of discernibility: the ability to distinguish between objects, based on their attribute values. It allows to infer data dependencies that are useful in the fields of feature selection and decision model construction. In many cases, however, it is...

This paper unifies theories of fuzzy systems, cognition, economic man and organization behavior in order to introduce cognitive machines. It contributes by outlining the impact of fuzzy theory on these fields which have been subject of Nobel Prize in Economics. This research advocates and explains that Fuzzy Theory involves the necessary mathematical and logical foundations which materialize th...

We investigate here a supermatrix model with a mass term and a cubic interaction. It is based on the super Lie algebra osp(1|32,R), which could play a rôle in the construction of the eleven-dimensional M-theory. This model contains a massive version of the IIB matrix model, where some fields have a tachyonic mass term. Therefore, the trivial vacuum of this theory is unstable. However, this mode...