Utilizing a new feed-back fuzzy neural network for solving a system of fuzzy equations

utilizing a new feed-back fuzzy neural network for solving a system of fuzzy equations

this paper intends to offer a new iterative method based on articial neural networks for finding solution of a fuzzy equations system. our proposed fuzzied neural network is a ve-layer feedback neural network that corresponding connection weights to output layer are fuzzy numbers. this architecture of articial neural networks, can get a real input vector and calculates its corresponding fu...

Utilizing a new feed-back fuzzy neural network for solving a system of fuzzy equations

In this paper, we intend to offer a new method based on fuzzy neural networks for finding a real solution of fuzzy equations system. Our proposed fuzzified neural network is a fivelayer feed-back neural network that corresponding connection weights to output layer are fuzzy numbers. The proposed architecture of artificial neural network, can get a real input vector and calculates it’s correspon...

A NEW ANALYTICAL METHOD FOR SOLVING FUZZY DIFFERENTIAL EQUATIONS

In the literature, several numerical methods are proposed for solvingnth-order fuzzy linear differential equations. However, till now there areonly two analytical methods for the same. In this paper, the fuzzy Kolmogorov'sdifferential equations, obtained with the help of fuzzy Markov modelof piston manufacturing system, are solved by one of these analytical methodsand illustrated that the obtai...

A New Iterative Method For Solving Fuzzy Integral ‎Equations

In the present work, by applying known Bernstein polynomials and their advantageous properties, we establish an efficient iterative algorithm to approximate the numerical solution of fuzzy Fredholm integral equations of the second kind. The convergence of the proposed method is given and the numerical examples illustrate that the proposed iterative algorithm are ‎valid.‎

A New Method for Solving Fuzzy Linear System

Solving Fuzzy Equations Using Neural Nets with a New Learning Algorithm

Artificial neural networks have the advantages such as learning, adaptation, fault-tolerance, parallelism and generalization. This paper mainly intends to offer a novel method for finding a solution of a fuzzy equation that supposedly has a real solution. For this scope, we applied an architecture of fuzzy neural networks such that the corresponding connection weights are real numbers. The ...