the purpose of this study was to evaluate three models of artificial neural networks (ann), regression trees (m5) and hargrives-samani (hg) in estimation of reference evapotranspiration. for this purpose was used climate information of sistan va baloochestan, kerman, yazd and khorasan jonoobi from 1998 to 2008. in addition to effect of wind (u) on evapotranspiration (et0), estimation of et0 was...

this paper reports on the use of artificial neural networks (ann) and partial least squareregression (pls) combined with nir spectroscopy (900-1700 nm) to design calibration models for thedetermination of sugar content in sugar beet. in this study a total of 80 samples were used as the calibration set,whereas 40 samples were used for prediction. three pre-processing methods, including multiplic...

accurate prediction of river flow is one of the most important factors in surface water recourses management especially during floods and drought periods. in fact deriving a proper method for flow forecasting is an important challenge in water resources management and engineering. although, during recent decades, some black box models based on artificial neural networks (ann), have been develop...

Artificial Neural Networks (ANN) consist an alternative method of solving complex problems. They operate as a “black box” model learning from examples, which is capable of dealing with non-linear problems and predicting results at high speed. An advantage of using ANN is their ability to handle large and complex systems with many interrelated parameters. They seem to simply ignore excess data t...

in recent years, artificial neural networks (anns) have become one of the most promising tools in order to model complex hydrological processes such as the rainfall-runoff process. in many studies, anns have demonstrated superior results compared to alternative methods. anns are able to map underlying relationship between input and output data without prior understanding of the process under in...

A multi-objective optimization (MOO) of two-element wing models with morphing flap by using computational fluid dynamics (CFD) techniques, artificial neural networks (ANN), and non-dominated sorting genetic algorithms (NSGA II), is performed in this paper. At first, the domain is solved numerically in various two-element wing models with morphing flap using CFD techniques and lift (L) and drag ...

The paper presents a comparison of lumped runoff modelling approaches, aimed at the realtime forecasting of flood events, based on or integrating Artificial Neural Networks (ANNs). ANNs are used in two ways: (a) as black-box type runoff simulation models or (b) for the real-time improvement of the discharge forecasts issued by a conceptual-type rainfall-runoff model. As far as the coupling of A...

This paper reports on the use of Artificial Neural Networks (ANN) and Partial Least Squareregression (PLS) combined with NIR spectroscopy (900-1700 nm) to design calibration models for thedetermination of sugar content in sugar beet. In this study a total of 80 samples were used as the calibration set,whereas 40 samples were used for prediction. Three pre-processing methods, including Multiplic...

Control chart pattern (CCP) recognition techniques are widely used to identify the potential process problems in modern industries. Recently, artificial neural network (ANN) –based techniques are very popular to recognize CCPs. However, finding the suitable architecture of an ANN-based CCP recognizer and its training process are time consuming and tedious. In addition, because of the black box ...