Transmission lines are generally subjected to faults, so it is advantageous to determine these faults as quickly as possible. This study uses an Artificial Neural Network technique to locate a fault as soon as it happens on the Doukan-Erbil of 132kv double Transmission lines network. CYME 7.1-Programming/Simulink utilized simulation to model the suggested network. A multilayer perceptron feed-forward artificial neural network with a back propagation learning algorithm is used for the intelligence locator's training, testing, assessment, and validation. Voltages and currents were applied as inputs during the neural network's training. The pre-fault and post-fault values determined the scaled values. The neural network's p

The present study develops an artificial neural network (ANN) to model an analysis and a simulation of the correlation between the average corrosion rate carbon steel and the effective parameter Reynolds number (Re), water concentration (Wc) % temperature (T o) with constant of PH 7 . The water, produced fom oil in Kirkuk oil field in Iraq from well no. k184-Depth2200ft., has been used as a corrosive media and specimen area (400 mm2) for the materials that were used as low carbon steel pipe. The pipes are supplied by Doura Refinery . The used flow system is all made of Q.V.F glass, and the circulation of the two –phase (liquid – liquid ) is affected using a Q.V.F pump .The input parameters of the model consists of Reynolds number , w

Wellbore instability and sand production onset modeling are very affected by Sonic Shear Wave Time (SSW). In any field, SSW is not available for all wells due to the high cost of measuring. Many authors developed empirical correlations using information from selected worldwide fields for SSW prediction. Recently, researchers have used different Artificial Intelligence methods for estimating SSW. Three existing empirical correlations of Carroll, Freund, and Brocher are used to estimate SSW in this paper, while a fourth new empirical correlation is established. For comparing with the empirical correlation results, another study's Artificial Neural Network (ANN) was used. The same data t

In this paper, the memorization capability of a multilayer interpolative neural network is exploited to estimate a mobile position based on three angles of arrival. The neural network is trained with ideal angles-position patterns distributed uniformly throughout the region. This approach is compared with two other analytical methods, the average-position method which relies on finding the average position of the vertices of the uncertainty triangular region and the optimal position method which relies on finding the nearest ideal angles-position pattern to the measured angles. Simulation results based on estimations of the mobile position of particles moving along a nonlinear path show that the interpolative neural network approach outperf

Some major pollutants of polycyclic aromatic hydrocarbons (PAH) those discharged as water produced (WP) from the AlAhdab oil field (AOF) in the ponds close to it may leak to the water resources around and eventually reaches the marshes which will affect its ecosystem. Thus, this work aims to track the availability of PAH in the water resources and the Main Outfall Drain (MOD) nearby. The determination of PAH was evaluated using “High-Performance Liquid Chromatography (HPLC)”. The mean concentration of sixteen PAH in the produced water within the field was relatively high (0.01 to 10.89 g/ml) with standard deviations of (0.10.9). While, PAH outside the field were gradually diminishes down to (0.01-0.039) x10-2 g/ml which exceeds th

Abstract

  Nowadays, the world adopts a philosophy that relates to environmental conservation. This philosophy can be achieved through providing environmentally friendly products while satisfying customers' needs as well. To attain that, a new systems and programs need to be applied in a scientific manner, and total quality environmental management (TQEM) is among these concepts. The research aimed to analyze the Relationship between (TQEM) Practices and its effect on Flexible Manufacturing in Badush factory. The research sample includes managers and head of divisions at top, middle and front line management levels which were (27) working in Badush factory. To achieve the objectives of the study, the descriptive anal

This paper deals with a preliminary survey helminth parasites of the black partridge. Francolinus francolinus arabistanicus in Baghdad area, middle of Iraq. It was found that the bird was infected with the cestodes Cotugnia digonopora and Raillietina tetragona with infection rates of 61.9% and 4.8% respectively, and the nematodes Heterakis gallinarum and Paroneoccrca rouss-lotti with infection rates of 4.8% and 19% respectively. Some important measurements, distribution and occurrence according host-sex of each parasite were provided along with some remarks on parasites biology.

Specialized hardware implementations of Artificial Neural Networks (ANNs) can offer faster execution than general-purpose microprocessors by taking advantage of reusable modules, parallel processes and specialized computational components. Modern high-density Field Programmable Gate Arrays (FPGAs) offer the required flexibility and fast design-to-implementation time with the possibility of exploiting highly parallel computations like those required by ANNs in hardware. The bounded width of the data in FPGA ANNs will add an additional error to the result of the output. This paper derives the equations of the additional error value that generate from bounded width of the data and proposed a method to reduce the effect of the error to give