The evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed structure has the ability to predict the response of dynamical systems more powerful than with the CNN. The proposed structure is more powerful than the CNN by 28.33% in terms of minimizing the root mean square error.
The dangers of (Israel's) integration with Arab countries in the middle east region will threaten the Arab security structure dimension, which the latter makes the Arab regional system vulnerable for distortion due to its nominal and symbolic value which is far from the Arab self and questioning with its effectiveness in comparing with the real capabilities to Arab countries in achieving the common targets. So, how to assess the different problems that began to hit the structure of the Arab regional system? and how to pledge an allegiance after putting forward what is known as the American Deal of the Century for the administration of former US President Donald Trump for making another step toward normalization with (Israel)?. The reveal
... Show MoreShort Multi-Walled Carbon Nanotubes functionalized with OH group (MWCNTs-OH) were used to synthesize flexible MWCNTs networks. The MWCNTs suspension was synthesized using Benzoquinone (BQ) and N, N Dimethylformamide alcohol (DMF) in specific values and then deposited on filter paper by filtration from suspension (FFS) method. Polypyrrole (PPy) conductive polymer doped with metallic nanoparticles (MNPs) prepared using in-situ chemical polymerization method. To improve the properties of the MWCNTs networks, a coating layer of (PPy) conductive polymer, PPy:Ag nanoparticles, and PPy: Cu nanoparticles were applied to the network. The fabricated networks were characterized using an X-ray diffractometer (XRD), UV-Vis. spectrometer, and Ato
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In this work, diabetic glucose concentration level control under disturbing meal has been controlled using two set of advanced controllers. The first set is sliding mode controllers (classical and integral) and the second set is represented by optimal LQR controllers (classical and Min-, ax). Due to their characteristic features of disturbance rejection, both integral sliding mode controller and LQR Minmax controller are dedicated here for comparison. The Bergman minimal mathematical model was used to represent the dynamic behavior of a diabetic patient’s blood glucose concentration to the insulin injection. Simulations based on Matlab/Simulink, were performed to verify the performance of each controll
... Show MoreWhen optimizing the performance of neural network-based chatbots, determining the optimizer is one of the most important aspects. Optimizers primarily control the adjustment of model parameters such as weight and bias to minimize a loss function during training. Adaptive optimizers such as ADAM have become a standard choice and are widely used for their invariant parameter updates' magnitudes concerning gradient scale variations, but often pose generalization problems. Alternatively, Stochastic Gradient Descent (SGD) with Momentum and the extension of ADAM, the ADAMW, offers several advantages. This study aims to compare and examine the effects of these optimizers on the chatbot CST dataset. The effectiveness of each optimizer is evaluat
... Show MoreArtificial Neural Networks (ANN) is one of the important statistical methods that are widely used in a range of applications in various fields, which simulates the work of the human brain in terms of receiving a signal, processing data in a human cell and sending to the next cell. It is a system consisting of a number of modules (layers) linked together (input, hidden, output). A comparison was made between three types of neural networks (Feed Forward Neural Network (FFNN), Back propagation network (BPL), Recurrent Neural Network (RNN). he study found that the lowest false prediction rate was for the recurrentt network architecture and using the Data on graduate students at the College of Administration and Economics, Univer
... Show MoreIn this paper, we derive and prove the stability bounds of the momentum coefficient µ and the learning rate ? of the back propagation updating rule in Artificial Neural Networks .The theoretical upper bound of learning rate ? is derived and its practical approximation is obtained
This paper is attempt to study the nonlinear second order delay multi-value problems. We want to say that the properties of such kind of problems are the same as the properties of those with out delay just more technically involved. Our results discuss several known properties, introduce some notations and definitions. We also give an approximate solution to the coined problems using the Galerkin's method.
Numerous regions in the city of Baghdad experience the congestion and traffic problems. Due to the religious and economic significance, Al-Kadhimiya city (inside the metropolitan range of Baghdad) was chosen as study area. The data gathering stage was separated into two branches: the questionnaire method which is utilized to estimate the traffic volumes for the chosen roads and field data collection method which included video recording and manual counting for the volumes entering the selected signal intersections. The stage of analysis and evaluation for the seventeen urban roads, one highway, and three intersections was performed by HCS-2000 software.The presented work plots a system for assessing the level of service
... Show MoreThe possibility of implementing smart mobility in the traditional city: Studying the possibility of establishing an intelligent transportation system in the city center of Kadhimiya
This study focuses on the implementation of interfaces for human machine interaction (HMI) control and monitor automatic production line. The automatic production line can performance feeding, transportation, sorting functions. The objectives of this study are implemented two SCADA/HMI system using two different software. TIA portal software is used to build HMI, alarm, and trends in touch panel which is helped an operator to control and monitor the production line. LabVIEW software is used to build HMI and trends in the computer screen and is linked with Microsoft Excel (ME) to generate information table helped to monitor the performance of the pneumatic equipment. The production line can do performance feeding, transportation, sorting fun
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