The duration of sunshine is one of the important indicators and one of the variables for measuring the amount of solar radiation collected in a particular area. Duration of solar brightness has been used to study atmospheric energy balance, sustainable development, ecosystem evolution and climate change. Predicting the average values of sunshine duration (SD) for Duhok city, Iraq on a daily basis using the approach of artificial neural network (ANN) is the focus of this paper. Many different ANN models with different input variables were used in the prediction processes. The daily average of the month, average temperature, maximum temperature, minimum temperature, relative humidity, wind direction, cloud level and atmospheric pressure were used as input parameters in order to obtain the daily average of sunshine duration (SD) as the output. The eight-year data were divided into two categories. The first category covers whole years (annually) and the second category is seasonal. To recognize and assess the influence of different input parameters on sunshine duration, six models of ANN have been evolved. The findings showed that in the annual models, the outcomes of RMSE, MAE and R for the model with input parameters (Month, Cloud Level and Average Temperature) were the best results 1.82, 1.175 and 0.89, respectively. As for the season models, the outcomes of RMSE, MAE and R for the autumn season were the best results 1.450, 1.009 and 0.94, respectively. Accordingly, the performance of the artificial neural network is considerably effective in predicting the sunshine duration.
The increase globally fossil fuel consumption as it represents the main source of energy around the world, and the sources of heavy oil more than light, different techniques were used to reduce the viscosity and increase mobility of heavy crude oil. this study focusing on the experimental tests and modeling with Back Feed Forward Artificial Neural Network (BFF-ANN) of the dilution technique to reduce a heavy oil viscosity that was collected from the south- Iraq oil fields using organic solvents, organic diluents with different weight percentage (5, 10 and 20 wt.% ) of (n-heptane, toluene, and a mixture of different ratio
... Show MoreThe consumption of dried bananas has increased because they contain essential nutrients. In order to preserve bananas for a longer period, a drying process is carried out, which makes them a light snack that does not spoil quickly. On the other hand, machine learning algorithms can be used to predict the sweetness of dried bananas. The article aimed to study the effect of different drying times (6, 8, and 10 hours) using an air dryer on some physical and chemical characteristics of bananas, including CIE-L*a*b, water content, carbohydrates, and sweetness. Also predicting the sweetness of dried bananas based on the CIE-L*a*b ratios using machine learn- ing algorithms RF, SVM, LDA, KNN, and CART. The results showed that increasing the drying
... Show MoreIt is well known that the rate of penetration is a key function for drilling engineers since it is directly related to the final well cost, thus reducing the non-productive time is a target of interest for all oil companies by optimizing the drilling processes or drilling parameters. These drilling parameters include mechanical (RPM, WOB, flow rate, SPP, torque and hook load) and travel transit time. The big challenge prediction is the complex interconnection between the drilling parameters so artificial intelligence techniques have been conducted in this study to predict ROP using operational drilling parameters and formation characteristics. In the current study, three AI techniques have been used which are neural network, fuzzy i
... Show MoreBuzurgan oil field suffers from the phenomenon of asphaltene precipitation. The serious negatives of this phenomenon are the decrease in production caused by clogging of the pores and decrease in permeability and wettability of the reservoir rocks, in addition to the blockages that occur in the pipeline transporting crude oil. The presence of laboratories in the Iraqi oil companies helped to conduct the necessary experiments, such as gas chromatography (GC) test to identify the components of crude oil and the percentages of each component, These laboratory results consider the main elements in deriving a new equation called modified colloidal instability index (MCII) equation based on a well-known global equation called colloidal instabi
... Show MoreThis research presents a method for calculating stress ratio to predict fracture pressure gradient. It also, describes a correlation and list ideas about this correlation. Using the data collected from four wells, which are the deepest in southern Iraqi oil fields (3000 to 6000) m and belonged to four oil fields. These wells are passing through the following formations: Y, Su, G, N, Sa, Al, M, Ad, and B. A correlation method was applied to calculate fracture pressure gradient immediately in terms of both overburden and pore pressure gradient with an accurate results. Based on the results of our previous research , the data were used to calculate and plot the effective stresses. Many equations relating horizontal effective stress and vertica
... Show MoreBuzurgan oil field suffers from the phenomenon of asphaltene precipitation. The serious negatives of this phenomenon are the decrease in production caused by clogging of the pores and decrease in permeability and wettability of the reservoir rocks, in addition to the blockages that occur in the pipeline transporting crude oil. The presence of laboratories in the Iraqi oil companies helped to conduct the necessary experiments, such as gas chromatography (GC) test to identify the components of crude oil and the percentages of each component, These laboratory results consider the main elements in deriving a new equation called modified colloidal instability index (MCII) equation based on a well-known global equation called colloidal in
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