over the last decade or so, artificial neural networks (anns) have become one of the most promising tools formodelling hydrological processes such as rainfall runoff processes. however, the employment of a single model doesnot seem to be an appropriate approach for modelling such a complex, nonlinear, and discontinuous process thatvaries in space and time. for this reason, this study aims at de...

the successful key of trading in the forex market is the selection of correct exchange in proper time based on an exact prediction of future exchange rate. foreign exchange rates are affected by many correlated economic, political and even psychological factors. therefore, in order to achieve a profitable trade these factors should be considered. the application of intelligent techniques for fo...

During the past few years, modeling in agriculture has attracted considerable attention. New modeling methods including neural networks are employed in various industries, and it is necessary that their use in agriculture be also considered. This research addressed the trend of energy use in broiler farms in Alborz Province and sought to model the trend of energy consumption and production in t...

This paper presents a review of applications of artificial neural networks in biomedical engineering area. Artificial neural networks in general are explained; some limitations and some proven benefits of neural networks are discussed. Use of art ificial neural network techniques in various biomedical engineering applications is summarised. A case study is used to demonstrate the efficacy of ar...

the purpose of this research is to detect manipulation of stock prices in tehran stock exchange that it has been done through hybrid genetic algorithm-artificial neural network (ann-ga) model and the simplified quadratic discriminant function (sqdf) model. in this study, the variables of price, trading volume and free float stock to match the results of the model and the actual data of price ma...

using image processing and artificial intelligence systems in agriculture and food industry is increasing daily. the purpose of this research is to study the feasibility of using image processing technique in predicting process of moisture content changes on green tea sheets during the drying using predictive artificial intelligence systems such as: artificial neural networks and adaptive neuro...

The prediction of the ultimate bearing capacity of the pile under axial load is one of the important issues for many researches in the field of geotechnical engineering. In recent years, the use of computational intelligence techniques such as different methods of artificial neural network has been developed in terms of physical and numerical modeling aspects. In this study, a database of 100 p...

estimate of sediment load is required in a wide spectrum of water resources engineering problems. the nonlinear nature of suspended sediment load series necessitates the utilization of nonlinear methods to simulate the suspended sediment load. in this study artificial neural networks (anns) are employed to estimate daily suspended sediment load. two different ann algorithms, multi layer percept...

Production of highly viscous tar sand bitumen using Steam Assisted Gravity Drainage (SAGD) with a pair of horizontal wells has advantages over conventional steam flooding. This paper explores the use of Artificial Neural Networks (ANNs) as an alternative to the traditional SAGD simulation approach. Feed forward, multi-layered neural network meta-models are trained through the Back-...