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joe-506
A Nonlinear MIMO-PID Neural Controller Design for Vehicle Lateral Dynamics model based on Modified Elman Neural Network
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This paper presents a new design of a nonlinear multi-input multi-output PID neural controller of the active brake steering force and the active front steering angle for a 2-DOF vehicle model based on modified Elman recurrent neural. The goal of this work is to achieve the stability and to improve the vehicle dynamic’s performance through achieving the desired yaw rate and reducing the lateral velocity of the vehicle in a minimum time period for preventing the vehicle from slipping out the road curvature by using two active control actions: the front steering angle and the brake steering force. Bacterial forging optimization algorithm is used to adjust the parameters weights of the proposed controller. Simulation results based Maltab package show the control methodology has effectiveness performance in terms of the excellent dynamic behavior of the vehicle model by minimizing the tracking error and smoothness control signals without saturation state obtained, especially when adding a bounded external disturbances to the vehicle model.

 

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Publication Date
Mon Jul 31 2017
Journal Name
Journal Of Engineering
Rigid Trunk Sewer Deterioration Prediction Models using Multiple Discriminant and Neural Network Models in Baghdad City, Iraq
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Publication Date
Tue Aug 01 2017
Journal Name
Journal Of Engineering
Rigid trunk sewer deterioration prediction models using multiple discriminant and neural network models in Baghdad city, Iraq
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The deterioration of buried sewers during their lifetime can be affected by several factors leading to bad performance and can damage the infrastructure similar to other engineering structures. The Hydraulic deterioration of the buried sewers caused by sewer blockages while the structural deterioration caused by sewer collapses due to sewer specifications and the surrounding soil characteristics and the groundwater level. The main objective of this research is to develop deterioration models, which are used to predict changes in sewer condition that can provide assessment tools for determining the serviceability of sewer networks in Baghdad city. Two deterioration models were developed and tested using statistical software SPSS, the

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Publication Date
Sat Jan 01 2022
Journal Name
3rd International Scientific Conference Of Alkafeel University (iscku 2021)
Investigations for the critical vehicle velocities on a curved path
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􀀨􀀅􀀆􀀔􀀜􀀄􀀂􀀆􀀈􀀓􀀌􀀩􀀏􀀆􀀉􀀅􀀆􀀉􀀅􀀉􀀚􀀝􀀔􀀄􀀗􀀉􀀚􀀆􀀂􀀓􀀚􀀁􀀔􀀄􀀓􀀅􀀆􀀄􀀂􀀆􀀔􀀓􀀆􀀃􀀂􀀔􀀄􀀟􀀉􀀔􀀃􀀆􀀔􀀜􀀃􀀆􀀛􀀃􀀜􀀄􀀗􀀚􀀃􀀆􀀗􀀌􀀄􀀔􀀄􀀗􀀉􀀚􀀆􀀂􀀘􀀃􀀃􀀊􀀂􀀆􀀓􀀖􀀆􀀓􀀛􀀃􀀌􀀔􀀁􀀌􀀅􀀄􀀅􀀕􀀢􀀆􀀪􀀜􀀃􀀆􀀄􀀅􀀛􀀃􀀂􀀔􀀄􀀕􀀉􀀔􀀄􀀓􀀅􀀂􀀆 􀀉􀀌􀀃􀀆􀀙􀀉􀀂􀀃􀀊􀀆􀀓􀀅􀀆􀀉􀀁􀀔􀀓􀀟􀀓􀀙􀀄􀀚􀀃􀀆􀀚􀀉􀀔􀀃􀀌􀀉􀀚􀀆􀀂􀀘􀀉􀀗􀀃􀀆􀀟􀀄􀀊􀀂􀀔􀀆􀀔􀀜􀀃􀀆􀀗􀀃􀀅􀀔􀀃􀀌􀀚􀀄􀀅􀀃􀀂􀀆􀀓􀀖􀀆􀀔􀀜􀀃􀀆􀀙􀀉􀀂􀀃􀀆

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
On Training Of Feed Forward Neural Networks
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In this paper we describe several different training algorithms for feed forward neural networks(FFNN). In all of these algorithms we use the gradient of the performance function, energy function, to determine how to adjust the weights such that the performance function is minimized, where the back propagation algorithm has been used to increase the speed of training. The above algorithms have a variety of different computation and thus different type of form of search direction and storage requirements, however non of the above algorithms has a global properties which suited to all problems.

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Publication Date
Wed Feb 15 2023
Journal Name
International Journal Of Emerging Technologies In Learning (ijet)
Instructional Design According to the Repulsive Learning Model and its Impact on the Achievement of Chemistry and Lateral Thinking for Third-Grade Intermediate Students
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Identify the effect of an educational design according to the repulsive (allosteric) learning model on the achievement of chemistry and lateral thinking. The sample consisted of (59) students from third-grade intermediate students. They were randomly distributed into two groups (experimental and control), and the equivalence was done in (chronological age, previous achievement in chemistry, intelligence, lateral thinking). The (30) students from experimental group were taught according to the instructional design, other 29 students from the (control) group were taught according to the usual method. Two tests done, one of them is an achievement test consisted of (30) items of the type of multiple choice, the other was a lateral think

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Publication Date
Fri Nov 01 2013
Journal Name
Al-nahrain Journal Of Science
Modified third order iterative method for solving nonlinear equations
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Many numerical approaches have been suggested to solve nonlinear problems. In this paper, we suggest a new two-step iterative method for solving nonlinear equations. This iterative method has cubic convergence. Several numerical examples to illustrate the efficiency of this method by Comparison with other similar methods is given.

Publication Date
Thu Aug 01 2024
Journal Name
Water Practice & Technology
Artificial neural network and response surface methodology for modeling oil content in produced water from an Iraqi oil field
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ABSTRACT<p>The majority of the environmental outputs from gas refineries are oily wastewater. This research reveals a novel combination of response surface methodology and artificial neural network to optimize and model oil content concentration in the oily wastewater. Response surface methodology based on central composite design shows a highly significant linear model with P value &lt;0.0001 and determination coefficient R2 equal to 0.747, R adjusted was 0.706, and R predicted 0.643. In addition from analysis of variance flow highly effective parameters from other and optimization results verification revealed minimum oily content with 8.5 ± 0.7 ppm when initial oil content 991 ppm, tempe</p> ... Show More
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Publication Date
Sat Sep 21 2013
Journal Name
Nonlinear Dynamics
BER performance enhancement for secure wireless optical communication systems based on chaotic MIMO techniques
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Publication Date
Fri Dec 31 2021
Journal Name
International Journal Of Intelligent Engineering And Systems
Performance Analysis for Hybrid Massive MIMO FSO/RF Links Based on Efficient Channel Codes
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Publication Date
Tue Jun 30 2020
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Using Artificial Neural Network to Predict Rate of Penetration from Dynamic Elastic Properties in Nasiriya Oil Field
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   The time spent in drilling ahead is usually a significant portion of total well cost. Drilling is an expensive operation including the cost of equipment and material used during the penetration of rock plus crew efforts in order to finish the well without serious problems. Knowing the rate of penetration should help in speculation of the cost and lead to optimize drilling outgoings. Ten wells in the Nasiriya oil field have been selected based on the availability of the data. Dynamic elastic properties of Mishrif formation in the selected wells were determined by using Interactive Petrophysics (IP V3.5) software based on the las files and log record provided. The average rate of penetration and average dynamic elastic propert

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