General Dual Fuzzy Linear Systems

Abstract This paper mainly intends to discuss the solution of fully fuzzy linear systems (FFLS) Ax + b = Cx + d, where A and C are fuzzy matrices, b and d are fuzzy vectors. We transform the systems by using fuzzy numbers with a new parametric form for finding a fuzzy vector x that satisfies in the system

Dry Needling Effects of the Upper Trapezius Muscle on the Angles and Range of Motion of the Neck in Individuals with Forward Head Posture

Introduction: Forward head posture (FHP) is one of the most common positional deviations. Frequent users often exhibit incorrect posture because of the rising popularity of media devices, such as smartphones and computers. This posture leads to changes in muscle activity in cervical flexion and extension. It is defined by hyperextension of the upper cervical vertebrae and forward translation of the cervical vertebrae. This study evaluates the effect of dry needles as a new method in the upper trapezius muscle on the neck’s angles and range of motion (ROM) in individuals with FHP. Materials and Methods: In this quasi-experimental interventional study, 18 women with FHP underwent a dry needle session. The photogrammetry of the cranio-vertebral angle measured the degree of FHP. Visual analog scale (VAS), pain pressure threshold (PPT), cranio-vertebral angle (CVA) and cranio-horizontal angles (CHA), ROM, scapular index (SI), and forward shoulder translation (FST) were assessed before and after the intervention. Results: The results demonstrated that after the intervention, right and left PPT, flexion, and proper neck rotation, right and left SI, CVA, and CHA were significantly improved (P<0.05). Conclusion: The results showed that one session of dry needling with stretching exercises intervention could improve PPT, ROM, SI, CVA, and CHA and consequently improve FHP

Quantification of R-Fuzzy sets

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 significance measure allows for an intermediary approach to that of a type-2 fuzzy set. By inspecting the returned significance degree of a particular membership value, one is able to ascertain its true significance in relation, relative to other encapsulated membership values. An R-fuzzy set coupled with the proposed significance measure allows for a type-2 fuzzy equivalence, an intermediary, all the while retaining the underlying sentiment of individual and general perspectives, and with the adage of a significantly reduced computational burden. Several human based perception examples are presented, wherein the significance degree is implemented, from which a higher level of detail can be garnered. The results demonstrate that the proposed research method combines the high capacity in uncertainty representation of type-2 fuzzy sets, together with the simplicity and objectiveness of type-1 fuzzy sets. This in turn provides a practical means for problem domains where a type-2 fuzzy set is preferred but difficult to construct due to the subjective type-2 fuzzy membership

A New Method for Solving General Dual Fuzzy Linear Systems

. According to fuzzy arithmetic, general dual fuzzy linear system (GDFLS) cannot be replaced by a fuzzy linear system (FLS). In this paper, we use new notation of fuzzy numbers and convert a GDFLS to two linear systems in crisp case, then we discuss complexity of the proposed method. Conditions for the existence of a unique fuzzy solution to n × n GDFLS are derive

A New Approach for Solving System of Fully Fuzzy Polynomial Equations

Abstract: In this paper, a new approach for solving system of fully fuzzy polynomial equations based on nonlinear programing (shown as NLP) with equality constrain is presented. It is easy to apply the proposed method. This method can also lead to improve numerical methods. In this work, an architecture of NLP is also proposed to find a fuzzy positive root of a system of fuzzy polynomial equations (if exists). Finally, we illustrate our approach by numerical examples

Solution of Fuzzy Matrix Equation System

The main is to develop a method to solve an arbitrary fuzzy matrix equation system by using the embedding approach. Considering the existing solution to fuzzy matrix equation system is done. To illustrate the proposed model a numerical example is given, and obtained results are discussed

Existence of Solution of Nonlinear Fuzzy Fredholm Integro-differential Equations

In this paper, we prove some results concerning the existence of solution of a class of nonlinear fuzzy Fredholm integro-differential equations. Also an iterative approach is proposed to obtain approximate solution of a class of nonlinear fuzzy Fredholm integro-differential equation of the second kind. A numerical example is presented to illustrate the proposed method

A new fuzzy regression model based on interval-valued fuzzy neural network and its applications to management

In this paper, a novel hybrid method based on interval-valued fuzzy neural network for approximate of interval-valued fuzzy regression models, is presented. The work of this paper is an expansion of the research of real fuzzy regression models. In this paper interval-valued fuzzy neural network (IVFNN) can be trained with crisp and interval-valued fuzzy data. Here a neural network is considered as a part of a large field called neural computing or soft computing. Moreover, in order to find the approximate parameters, a simple algorithm from the cost function of the fuzzy neural network is proposed. Finally, we illustrate our approach by some numerical examples and compare this method with existing methods

Solving the Second Order Fuzzy Differential Equations by Fuzzy Neural Network

In this paper, we interpret a two-point initial value problem for a second order fuzzy differential equation. We investigate a problem of finding a numerical approximation of the solution by using fuzzy neural network. Here neural network is considered as a part of a larger field called neural computing or soft computing. Finally, we illustrate our approach on an applied example in engineering