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...

the discharge or runoff which ousts from a watershed is important. because its deficiency leads to financial losses and its excesses cause damage in lives and property as flood. in this research using artificial neural network multi-layer perceptron (mlp (and adaptive neuro-fuzzy interface system (anfis) and multiple regression method simulated rainfall- runoff process on daily basis in the kho...

The objective of this study is to design a robust direct model reference adaptive controller (DMRAC) for a nonlinear cardiovascular model over a range of plant parameters representing a variety of physical conditions. The direct adaptive controllers used in thisd study require the plant to be almost strictly positive real (ASPR) that is, for a plant to be controlled there must exist a feedback ...

nowadays, credit risk is recognized as one of the most important bankruptcy factors of banks and financial institutions. in order to manage and control this risk, design of credit rating models is undeniable necessity. credit rating is used to identify the probability of credit default and on the other side classify the customers into two groups: good and bad accounts. until now, various statis...

In this paper the performance of Artificial Neural Networks (ANNs) and Adaptive Neuro- Fuzzy Inference Systems (ANFIS) in simulating the inverse dynamic behavior of Magneto- Rheological (MR) dampers is investigated. MR dampers are one of the most applicable methods in semi active control of seismic response of structures. Various mathematical models are introduced to simulate the dynamic behavi...

In this paper, we present a recurrent neural network model for solving CCR Model in Data Envelopment Analysis (DEA). The proposed neural network model is derived from an unconstrained minimization problem. In the theoretical aspect, it is shown that the proposed neural network is stable in the sense of Lyapunov and globally convergent to the optimal solution of CCR model. The proposed model has...