in order to comparing geostatistics and artificial neural networks (ann) methods in predicting soil salinity and clay content this experiment was conducted in sistan region land. 121 soil samples were taken at the depth of 0-30 cm within the grid of 750 750 m and soil ec and clay percent were determined. 105 samples were used for training and 16 samples were used for test in both models. diffe...

This work develops Artificial Neural Networks (ANN) models applied to predict the consumption forecasting considering climatic factors. It is intended to verify the influence of climatic factors on the electricity consumption forecasting through the ANN. The case study is applied in the Campinas city, Brazil. This work used Perceptron and Backpropagation ANN models. The specific goal is compari...

The primary objective of this research is to obtain an accurate forecasting model for the US presidential election. To identify a reliable model, artificial neural networks (ANN) and support vector regression (SVR) models are compared based on some specified performance measures. Moreover, six independent variables such as GDP, unemployment rate, the president’s approval rate, and others are co...

Accurate estimation of evaporation is important for design, planning and operation of water systems. In arid zones where water resources are scarce, the estimation of this loss becomes more interesting in the planning and management of irrigation practices. This paper investigates the ability of artificial neural networks (ANNs) technique to improve the accuracy of daily evaporation estimation....

In this study, a combined electro-(Fenton/coagulation/flotation) (EF/EC/El) process was studied via degradation of Disperse Orange 25 (DO25) organic dye as a case study. Influences of seven operational parameters on the dye removal efficiency (DR%) were measured: initial pH of the solution (pH0), applied voltage between the anode and cathode (V), initial ferrous ion concentration (CFe), initial...

Artificial neural networks (ANNs) are essentially a ‘black box’ technology. The lack of an explanation component prevents the full and complete exploitation of this form of machine learning. This chapter presents an historical perspective on rule extraction from artificial neural networks beginning with 6 ways in which the ANN paradigm may be enriched through the addition of rule extraction / e...

Although CO2 injection is one of the most common methods in enhanced oil recovery, it could alter fluid properties of oil and cause some problems such as asphaltene precipitation. The maximum amount of asphaltene precipitation occurs near the fluid pressure and concentration saturation. According to the description of asphaltene deposition onset, the bubble point pressure has a very special imp...