today, stock investment has become an important mean of national finance. apparently, it is significant for investors to estimate the stock price and select the trading chance accurately in advance, which will bring high return to stockholders. in the past, long-term trading processes and many technical analysis methods for stock market were put forward. however, stock market is a nonlinear sys...

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 ...

Communication protocols issues are one of the effective factors in communicated networks performance. One of challenging problem in CMT-SCTP which sends data by multipath concurrently is Receive Buffer Blocking. This problem has important role in data transmission speed in computer networks. In this paper, we propose a control method based on fuzzy logic so that can solve Receive Buffer Blockin...

In this paper, we are trying to examine trade offs between fuzzy logic and certain Bayesian networks and we propose to combine their respective advantages into fuzzy certain Bayesian networks (FCBN), a certain Bayesian networks of fuzzy random variables. This paper deals with different definitions and classifications of uncertainty, sources of uncertainty, and theories and methodologies present...

in this article different types of artificial neural networks (ann) were used for cntfet (carbon nanotube transistors) simulation. cntfet is one of the most likely alternatives to silicon transistors due to its excellent electronic properties. in determining the accurate output drain current of cntfet, time lapsed and accuracy of different simulation methods were compared. the training data for...

In this paper, global robust stability of stochastic impulsive recurrent neural networks with time-varyingdelays which are represented by the Takagi-Sugeno (T-S) fuzzy models is considered. A novel Linear Matrix Inequality (LMI)-based stability criterion is obtained by using Lyapunov functional theory to guarantee the asymptotic stability of uncertain fuzzy stochastic impulsive recurrent neural...

Fuzzy associative memories belong to the class of fuzzy neural networks that employ fuzzy operators such as fuzzy conjunctions, disjunctions, and implications in order to store associations of fuzzy patterns. Fuzzy associative memories are generally used to implement fuzzy rule-based systems. Applications of FAMs include backing up a truck and trailer, target tracking, human-machine interfaces,...

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 ...