Organizations expose to financial risk that can lead to bankruptcy and loss of business is increased nowadays. This may leads to discontinuity in operations, increased legal fees, administrative costs and other indirect costs. Accordingly, the purpose of this study was to predict the financial crisis of Tehran Stock Exchange using neural network and genetic algorithm. This research is descripti...

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...

in this study, response surface methodology (rsm) was used to optimize osmo-dehydration of orange slice. effect of osmotic solution temperature in the range of 30 to 60 °c, immersion time from 0 to 300 min and sucrose concentration from 35 to 65 brix degree on water loss, solid gain, moisture content, water loss to solid gain ratio and brix change were investigated by central composite design (...

An artificial neural network was used to optimize the release of salbutamol sulfate from hydrophilic matrix formulations. Model formulations to be used for training, testing and validating the neural network were manufactured with the aid of a central composite design with varying the levels of Methocel® K100M, xanthan gum, Carbopol® 974P and Surelease® as the input factors. In vitro dissolutio...

â  the prediction of maximum temperatures as one of the most important climatic parameters due to climate change, global warming and the recent drought will provide definitely more opportunity for planning and the provision of necessary arrangements for the planners. maximum temperatures are much important in management of natural and water resources, agriculture, development of pests and disea...

A new Markov-based method for real time prediction of network transmission time delays is introduced. The method considers a Multi-Layer Perceptron (MLP) neural model for the transmission network, where the number of neurons in the input layer is minimized so that the required calculations are reduced and the method can be implemented in the real-time. For this purpose, the Markov process order...

This paper introduces a change in the structure of an artificial neuron (McCulloch and Pitts), to improve the performance of the feed forward artificial neural networks like the multi-layer perceptron networks. Results on function approximation task and three pattern recognition problems show that the performance of a neural network can be improved by a simple change in its traditional structur...

The authors have investigated some potential applications of artificial neural networks in electrocardiografic (ECG) signal prediction. For this, the authors used an adaptive multilayer perceptron structure to predict the signal. The proposed procedure uses an artificial neural network based learning structure to estimate the (n+1)th sample from n previous samples To train and adjust the networ...