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A HYBRID CUCKOO SEARCH AND BACK-PROPAGATION ALGORITHMS WITH DYNAMIC LEARNING RATE TO SPEED UP THE CONVERGENCE (SUBPL) ALGORITHM
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BP algorithm is the most widely used supervised training algorithms for multi-layered feedforward neural net works. However, BP takes long time to converge and quite sensitive to the initial weights of a network. In this paper, a modified cuckoo search algorithm is used to get the optimal set of initial weights that will be used by BP algorithm. And changing the value of BP learning rate to improve the error convergence. The performance of the proposed hybrid algorithm is compared with the stan dard BP using simple data sets. The simulation result show that the proposed algorithm has improved the BP training in terms of quick convergence of the solution depending on the slope of the error graph.

Publication Date
Thu Feb 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Conceptual perspective of self-marketing Search descriptive
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Basic orientation is to look at identifying conceptual perspective to market self-research and descriptive, as has the marketing theme for the same attention in the practical side before endo scopic In recent years, is marketing an integrated and holistic included many areas not limited to the marketing of goods and services, and even included the marketing of religion, politics and individuals for themselves, as the awareness and concepts that seep into the soul of man from its inception until his arrival to the stage of owning a level of skills or expertise, scientific or all of those things degrees mixed with ambition and aspiration for self-realization takes way to search for opportunities or created, often observe individual

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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
DYNAMIC MODELING FOR DISCRETE SURVIVAL DATA BY USING ARTIFICIAL NEURAL NETWORKS AND ITERATIVELY WEIGHTED KALMAN FILTER SMOOTHING WITH COMPARISON
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Survival analysis is widely applied in data describing for the life time of item until the occurrence of an event of interest such as death or another event of understudy . The purpose of this paper is to use the dynamic approach in the deep learning neural network method, where in this method a dynamic neural network that suits the nature of discrete survival data and time varying effect. This neural network is based on the Levenberg-Marquardt (L-M) algorithm in training, and the method is called Proposed Dynamic Artificial Neural Network (PDANN). Then a comparison was made with another method that depends entirely on the Bayes methodology is called Maximum A Posterior (MAP) method. This method was carried out using numerical algorithms re

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Publication Date
Mon Dec 01 2008
Journal Name
Iraqi Journal Of Physics,2008
optical pulse propagation in photonic bandgap fiber Bragg grating
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Abstract: In this work we demonstrate and investigate the optical pulse propagation in a photonic band gap fiber Bragg grating (FBG). The light propagates in opposite direction in FBG is explained and discussed by a Coupled Mode Theory (CMT). The photonic band gap (stop band gap) is created by fabricated, a Bragg grating in optical fiber. The results show the pulse spectrum falls entirely within the stop band gap, the entire pulse is reflected by the grating, while when the pulse spectrum is outside the stop band gap the pulses will transmitted through the grating. The group velocity (VG) becomes zero at the edges of the stop band and group velocity dispersion β2 is anomalous on the shorter side of stop band gap whereas β2 for uniform fi

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Publication Date
Fri May 01 2020
Journal Name
Journal Of Electrical And Electronics Engineering
HF Wave Propagation Prediction Based On Passive Oblique Ionosonde
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High frequency (HF) communications have an important role in long distances wireless communications. This frequency band is more important than VHF and UHF, as HF frequencies can cut longer distance with a single hopping. It has a low operation cost because it offers over-the-horizon communications without repeaters, therefore it can be used as a backup for satellite communications in emergency conditions. One of the main problems in HF communications is the prediction of the propagation direction and the frequency of optimum transmission (FOT) that must be used at a certain time. This paper introduces a new technique based on Oblique Ionosonde Station (OIS) to overcome this problem with a low cost and an easier way. This technique uses the

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Publication Date
Mon Jul 01 2019
Journal Name
Materials Research Express
SiC composite based selective electromagnetic propagation for GHz application
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Publication Date
Tue Sep 01 2009
Journal Name
Al-khwarizmi Engineering Journal
Propagation Mechanisms for Surface Initiated Cracking in Composite Pavements
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The primary objective of this study was to identify the mechanisms for the development and propagation of longitudinal cracks that initiate at the surface of composite pavement. In this study the finite element program ANSYS version (5.4) was used and the model worked out using this program has the ability to analyze a composite pavement structure of different layer properties. Also, the aim of this study was modeling and analyzing of the composite pavement structure with the physical presence of crack induced in concrete underlying layer. The results obtained indicates that increasing the thickness of the asphalt layer tends to decrease the stress intensity factor, which may be attributed to the rapidly decrease of horizontal tensile st

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Publication Date
Thu Jun 28 2018
Journal Name
2018 4th International Conference On Computer And Technology Applications (iccta)
Improving accuracy of CADx system by hybrid PCA and backpropagation
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—Medical images have recently played a significant role in the diagnosis and detection of various diseases. Medical imaging can provide a means of direct visualization to observe through the human body and notice the small anatomical change and biological processes associated by different biological and physical parameters. To achieve a more accurate and reliable diagnosis, nowadays, varieties of computer aided detection (CAD) and computer-aided diagnosis (CADx) approaches have been established to help interpretation of the medical images. The CAD has become among the many major research subjects in diagnostic radiology and medical imaging. In this work we study the improvement in accuracy of detection of CAD system when comb

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Publication Date
Tue Aug 06 2024
Journal Name
Journal Of Thermal Analysis And Calorimetry
Al2O3–Cu hybrid nanofluid flow and heat transfer characteristics in the duct with various triangular rib configurations
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Publication Date
Sun Feb 28 2021
Journal Name
Journal Of Economics And Administrative Sciences
The use of the genetic algorithm to estimate the parameters function of the hypoexponential distribution by simulation
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In this research, the focus was placed on estimating the parameters of the Hypoexponential distribution function using the maximum likelihood method and genetic algorithm. More than one standard, including MSE, has been adopted for comparison by Using the simulation method

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Publication Date
Thu Jan 31 2019
Journal Name
Journal Of Engineering
Design of New Hybrid Neural Structure for Modeling and Controlling Nonlinear Systems
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This paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number

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