As Photovoltaic (PV) energy is impacted by various weather variables such as solar radiation and temperature, one of the key challenges facing forecasting choosing right inputs to achieve most accurate prediction. Weather datasets, past power data sets, or both sets can be utilized build different models. However, operators grid-connected PV farms do not always have full available them especial...

The paper presents a method for classifying coffees according to their scents using artificial neural network (ANN). The proposed method of uses genetic algorithm (GA) to determine the optimal parameters and topology of ANN. It uses adaptive back-propagation to accelerate the training process so that the entire optimization process can be achieved in an accelerated time. The optimized ANN has s...

pervious concrete is a concrete mixture prepared from cement, aggregates, water, little or no fines, and in some cases admixtures. the hydrological property of pervious concrete is the primary reason for its reappearance in construction. much research has been conducted on plain concrete, but little attention has been paid to porous concrete, particularly to the analytical prediction modeling o...

introduction: commitment of staff is intangible asset that can highly provide better services. since providing healthcare services is only possible through efficient human resources, this study evaluated the association between person-organization fit and organizational commitment of staff in university hospitals of tehran university of medical sciences, iran. methods: this was a descriptive an...

static deformation modulus is recognized as one of the most important parameters governing the behavior of rock masses. predictive models for the mechanical properties of rock masses have been used in rock engineering because direct measurement of the properties is difficult due to time and cost constraints. in this method the deformation modulus is estimated indirectly from classification syst...

A new hybrid model which combines wavelets and Artificial Neural Network (ANN) called wavelet neural network (WNN) model was proposed in the current study and applied for time series modeling of river flow. The time series of daily river flow of the Malaprabha River basin (Karnataka state, India) were analyzed by the WNN model. The observed time series are decomposed into sub-series using discr...