background and objectives: efficient cost management in hospitals’ pharmaceutical inventories have thepotential to remarkably contribute to optimization of overall hospital expenditures. to this end, reliable forecasting models for accurate prediction of future pharmaceutical demands are instrumental. while the linear methods are frequently used for forecasting purposes chiefly due to their sim...

contamination of water by heavy metals is a global problem. nowadays everybody knows that heavy metal ions consist of iron, lead, manganese, zinc, copper, cadmium, and nickel and so on they are common contaminants in wastewater and known to be toxic and carcinogenic that lead to many problems for human and water environment. in this research, experiments have been performed in the batch system ...

The Artificial Neural Network (ANN) is a powerful data-driven model that can capture and represent both linear and non-linear relationships between input and output data. Hence, ANNs have been widely used for the prediction and forecasting of water quality variables, to treat the uncertainty of contaminant source, and nonlinearity of water quality data. However, the initial weight parameter pro...

A fault section in Korean distribution networks is generally determined as a between switch with indicator (FI) and without an FI. However, the existing method cannot be applied to distributed generations (DGs) due false FIs that are generated by currents flowing from load side of location. To identify make applicable, this paper proposes determine utilizing artificial neural network (ANN) mode...

this study investigates the oil extraction from pistacia khinjuk by the application of enzyme.artificial neural network (ann) and adaptive neuro fuzzy inference system (anfis) were applied formodeling and prediction of oil extraction yield. 16 data points were collected and the ann was trained with onehidden layer using various numbers of neurons. a two-layered ann provides the best results, us...

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...

This study focuses on the development and performance of a comprehensive artificial neural network (ANN) model for the analysis of jointed concrete slabs under simultaneous aircraft and temperature loading. Using the results of the ILLI-SLAB finite element program, a comprehensive artificial neural network model was trained for the different loading conditions of gear loading only, temperature ...