In this study, activated sludge process for wastewater treatment in a refinery was investigated. For such purpose, a laboratory scale rig was built. The effect of several parameters such as temperature, residence time, effect of Leca (filling-in percentage of the reactor by Leca) and UV radiation on COD removal efficiency were experimentally examined. Maximum COD removal efficiency was obtained...

infiltration rate is one of the most important soil physical parameters and is a basic input data in irrigation and drainage projects. although, a number of theoretical or experimental based equations are presented to describe this phenomenon but the evaluation of some new sciences such as artificial neural networks, for prediction of the phenomenon can be investigated. generally, the infiltrat...

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...

abstract background: a computer aided diagnosis system was established using the wavelet transform and neural network to differentiate malignant from benign in a   group of patients with histo-pathologically proved breast lesions based on the data derived independ­ently from time-intensity profile.   materials and methods: the per­formance of the artificial neural network (ann) was evaluated us...

the effects of different climatic, soil, geometric, and management factors on soil organic carbon (soc) degradation and sequestration potential was evaluated in the semi-arid zone of mereg watershed, west of iran. two nonparametric methods, viz. classification and regression tree (cart) and feed forward back propagation artificial neural network (ann) were compared with parametric multivariate ...

abstract from longley, the various equations for determining the runoff to water management are presented by the researchers that are widely used in hydrologic sciences. in this study by using observational data, was evaluated empirical, artificial neural network (ann) and ca-active neuro-fuzzy inference system (canfis) models in estimation of runoff. for this purpose, by using climatic and phy...

as is well known, estimating parameters of the tree-parameter weibull distribution is a complicated task and sometimes contentious area with several methods vying for recognition. weibull distribution involves in reliability studies frequently and has many applications in engineering. however estimating the parameters of weibull distribution is crucial in classical ways. this distribution has t...

Permeability can be directly measured using cores taken from the reservoir in the laboratory. Due to high cost associated with coring, cores are available in a limited number of wells in a field. Many empirical models, statistical methods, and intelligent techniques were suggested to predict permeability in un-cored wells from easy-to-obtain and frequent data such as wireline logs. The main obj...

The paper deals with Data Envelopment Analysis (DEA) and Artificial Neural Network (ANN). We believe that solving for the DEA efficiency measure, simultaneously with neural network model, provides a promising rich approach to optimal solution. In this paper, a new neural network model is used to estimate the inefficiency of DMUs in large datasets.