changes in the physicochemical conditions of process unit, even under control, may lead to what are generically referred to as faults. the cognition of causes is very important, because the system can be diagnosed and fault tolerated. in this article, we discuss and propose an artificial neural network that can detect the incipient and gradual faults either individually or mutually. the main fe...

in this study, artificial neural network was used to predict the surface tension of 20 hydrocarbon mixtures. experimental data was divided into two parts (70% for training and 30% for testing). optimal configuration of the network was obtained with minimization of prediction error on testing data. the accuracy of our proposed model was compared with four well-known empirical equations. the arti...

Feed-forward neural networks are popular classification tools which are broadly used for early detection and diagnosis of breast cancer. In recent years, a great attention has been paid to bio-inspired optimization techniques due to its robustness, simplicity and efficiency in solving complex optimization problems. In this paper, it is intended to introduce a Genetic Algorithm based Firefly Alg...

in this work, response surface methodology (rsm) and artificial neural network (ann) were used to predict the decolorization efficiency of reactive red 33 (rr 33) by o3/uv process in a bubble column reactor. the effects of four independent variables including time (20-60 min), superficial gas velocity (0.06-0.18 cm/s), initial concentration of dye (50-150 ppm) and ph (3-11) were investigated us...

This paper presents an efficient optimization procedure to find the optimal shapes of double curvature  arch  dams  considering  fluid–structure  interaction  subject  to  earthquake  loading. The optimization is carried out using a combination of the magnetic charged system search, big bang-big crunch algorithm and artificial neural network methods. Performing the finite element  analysis  dur...

the main purpose of this paper is prediction of tse corporate financial bankruptcy using artificial neural networks. the mean values of key ratios reported in past bankruptcy studies were selected for neural network inputs (working capital to total assets, net income to total assets, total debt to total assets, current assets to current liabilities, quick assets to current liabilities). the neu...