<span lang="EN-US">This paper presents the comparison between optimized unscented Kalman filter (UKF) and optimized extended Kalman filter (EKF) for sensorless direct field orientation control induction motor (DFOCIM) drive. The high performance of UKF and EKF depends on the accurate selection of state and noise covariance matrices. For this goal, multi objective function genetic algorithm is used to find the optimal values of state and noise covariance matrices. The main objectives of genetic algorithm to be minimized are the mean square errors (MSE) between actual and estimation of speed, current, and flux. Simulation results show the optimal state and noise covariance matrices can improve the estimation of speed, current, t

Efficient management of treated sewage effluents protects the environment and reuse of municipal, industrial, agricultural and recreational as compensation for water shortages as a second source of water. This study was conducted to investigate the overall performance and evaluate the effluent quality from Al- Rustamiya sewage treatment plant (STP), Baghdad, Iraq by determining the effluent quality index (EQI). This assessment included daily records of major influent and effluent sewage parameters that were obtained from the municipal sewage plant laboratory recorded from January 2011 to December 2018. The result showed that the treated sewage effluent quality from STP was within the Iraqi quality standards (IQS) for disposal and t

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

Abstract

     Machining residual stresses correlate very closely with the cutting parameters and the tool geometries. This research work aims to investigate the effect of cutting speed, feed rate and depth of cut on the surface residual stress of steel AISI 1045 after face milling operation. After each milling test, the residual stress on the surface of the workpiece was measured by using X-ray diffraction technique. Design of Experiment (DOE) software was employed using the response surface methodology (RSM) technique with a central composite rotatable design to build a mathematical model to determine the relationship between the input variables and the response. The results showed that both

 Researchers have increased interest in recent years in determining the optimum sample size to obtain sufficient accuracy and estimation and to obtain high-precision parameters in order to evaluate a large number of tests in the field of diagnosis at the same time. In this research, two methods were used to determine the optimum sample size to estimate the parameters of high-dimensional data. These methods are the Bennett inequality method and the regression method. The nonlinear logistic regression model is estimated by the size of each sampling method in high-dimensional data using artificial intelligence, which is the method of artificial neural network (ANN) as it gives a high-precision estimate commensurate with the dat

Precision is one of the main elements that control the quality of a geodetic network, which defines as the measure of the network efficiency in propagation of random errors. This research aims to solve ZOD and FOD problems for a geodetic network using Rosenbrock Method to optimize the geodetic networks by using MATLAB programming language, to find the optimal design of geodetic network with high precision. ZOD problem was applied to a case study network consists of 19 points and 58 designed distances with a priori deviation equal to 5mm, to determine the best points in the network to consider as control points. The results showed that P55 and P73 having the minimum ellipse of error and considered as control points. FOD problem was applie

Nanoparticles (NPs) based techniques have shown great promises in all fields of science and industry. Nanofluid-flooding, as a replacement for water-flooding, has been suggested as an applicable application for enhanced oil recovery (EOR). The subsequent presence of these NPs and its potential aggregations in the porous media; however, can dramatically intensify the complexity of subsequent CO2 storage projects in the depleted hydrocarbon reservoir. Typically, CO2 from major emitters is injected into the low-productivity oil reservoir for storage and incremental oil recovery, as the last EOR stage. In this work, An extensive serious of experiments have been conducted using a high-pressure temperature vessel to apply a wide range of CO2-pres

Owing to the energy crisis and pollution problems of today, investigations have concentrated on
decreasing fuel consumption and on lowering the concentration of toxic components in combustion
products by using non-petroleum, renewable, sustainable and non-polluting fuels. While conventional energy sources such as natural gas, oil and coal are non-renewable, alcohol can be coupled to renewable and sustainable energy sources.
In this study, the combustion characteristics of diesel fuel and methanol blends were compared.
The tests were performed at steady state conditions in a four-cylinder DI diesel engine at full load at
1500-rpm engine speed. The experimental results showed that diesel methanol blends provided
12.7% inc

These days, it is crucial to discern between different types of human behavior, and artificial intelligence techniques play a big part in that.  The characteristics of the feedforward artificial neural network (FANN) algorithm and the genetic algorithm have been combined to create an important working mechanism that aids in this field. The proposed system can be used for essential tasks in life, such as analysis, automation, control, recognition, and other tasks. Crossover and mutation are the two primary mechanisms used by the genetic algorithm in the proposed system to replace the back propagation process in ANN. While the feedforward artificial neural network technique is focused on input processing, this should be based on the proce