This research has been done with the aim of identification of effective factors which influence on credit risk and designing model for estimating credit rating of the companies which have borrowed from a commercial bank in the one-year period by using Data Envelopment Analysis and neural network model and comparison of these two models . For this purpose, the necessary sample data on financial ...

In this paper, two kinds of chaotic neural networks are proposed to evaluate the efficiency of chaotic dynamics in robust pattern recognition. The First model is designed based on natural selection theory. In this model, attractor recurrent neural network, intelligently, guides the evaluation of chaotic nodes in order to obtain the best solution. In the second model, a different structure of ch...

Flood is a kind of natural disaster which causes financial damages and fatality for people. Every year, especially in areas like Maroon river basin which have changes in precipitation and temperatures, along with frequent and severe floods. This study aimed to identify the climatic parameters on flood area can be efficiently artificial neural network, better methods applied in anticipation of t...

     Electrical conductivity (EC) is an important factor in river engineering, especially studying of river water quality. In this study we studied and evaluated wavelet neural network to predict the electrical conductivity of the Kakareza river (in lorestan), and the results were compared with results of artificial neural network model. For this purpose, hydrogen carbonate, chloride, sulfate, ...

Estimating spatial distribution of precipitation is vital to execute water resources plans, drought, land-use plans environment, watershed management, and agricultural master plans. High variation in amount of precipitation in various parts, lack of measurement stations, and the complexity of relationship between precipitation and parameters affecting it have doubled the importance of developin...