Preferred Language
Articles
/
joe-2996
MODIFIED TRAINING METHOD FOR FEEDFORWARD NEURAL NETWORKS AND ITS APPLICATION in 4-LINK SCARA ROBOT IDENTIFICATION
...Show More Authors

In this research the results of applying Artificial Neural Networks with modified activation function to
perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance
Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of
identification strategy consists of a feed-forward neural network with a modified activation function that
operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have
been trained online and offline have been used, without requiring any previous knowledge about the
system to be identified. The activation function that is used in the hidden layer in FFNN is a modified
version of the wavelet function. This approach has been performed very successfully, with better results
obtained with the FFNN with modified wavelet activation function (FFMW) when compared with classic
FFNN with Sigmoid activation function (FFS) .One can notice from the simulation that the FFMW can be
capable of identifying the 4-Links of SCARA robot more efficiently than the classic FFS.

Crossref
View Publication Preview PDF
Quick Preview PDF
Publication Date
Mon Jun 01 2009
Journal Name
Journal Of Economics And Administrative Sciences
Suggested method for modifying the site parameter
...Show More Authors

     Estimating multivariate location and scatter with both affine equivariance and positive break down has always been difficult. Awell-known estimator which satisfies both properties is the Minimum volume Ellipsoid Estimator (MVE) Computing the exact (MVE) is often not feasible, so one usually resorts to an approximate Algorithm. In the regression setup, algorithm for positive-break down estimators like Least Median of squares typically recomputed the intercept at each step, to improve the result. This approach is called intercept adjustment. In this paper we show that a similar technique, called location adjustment, Can be applied to the (MVE). For this purpose we use the Minimum Volume Ball (MVB). In order

... Show More
View Publication Preview PDF
Crossref
Publication Date
Sat Jan 01 2011
Journal Name
Journal Of Engineering
FINITE ELEMENT METHOD FOR INCOMPRESSIBLE VISCOELASTIC MATERIALS
...Show More Authors

A numerical method (F.E.)was derived for incompressible viscoelastic materials, the aging and
environmental phenomena especially the temperature effect was considered in this method. A
treatment of incompressibility was made for all permissible values of poisons ratio. A
mechanical model represents the incompressible viscoelastic materials and so the properties can
be derived using the Laplace transformations technique .A comparison was made with the other
methods interested with viscoelastic materials by applying the method on a cylinder of viscoelastic material surrounding by a steel casing and subjected to a constant internal pressure, as well as a comparison with another viscoelastic method and for Asphalt Concrete pro

... Show More
View Publication Preview PDF
Crossref
Publication Date
Thu Dec 01 2022
Journal Name
Baghdad Science Journal
Synthesis, Spectral Identification, Antibacterial Evaluationand Theoretical Study of Co, Fe, Rh and Pd Complexes for 2-benzoylthiobenzimidazol
...Show More Authors

A new novel series of metalcomplexes are prepared from reactions between 2-benzoylthio- benzimidazole (L) with metal salts of Co (II) , Fe(III) and Rh (III) , while Pd(II) complex was obtained by mixing ligandsof 2-benzoylthiobenzimidazole (L) as primary ligand and bipyridine (L/)as secondary ligand as well as palladium chloride as metal salt in an ethanoic medium. The geometry of these compounds were identified using C.H.N.microanalysis, Ultraviolet–visible, Fourier transforms infrared, magnetic susceptibility, molar conductivity and flame atomic absorption (A.A). From the dataobtained by these spectral analyses, the molecular structures for Rh and Fe complexes were proposed to be octahedral geometry. A square planar const

... Show More
View Publication Preview PDF
Scopus (5)
Scopus Clarivate Crossref
Publication Date
Mon Mar 02 2015
Journal Name
Chemistry And Materials Research
Synthesis and Characterization of 3,5-Dimethyl-2- (4-nitrophenyl azo)-PhenolComplexes with Co(II) and Ni(II) and Study Its Effect on the Activity of AchEnzyme(invitro)
...Show More Authors

Transition metal complexes of Co(II) and Ni(II) with azo dye 3,5-dimethyl-2-(4-nitrophenylazo)-phenol derived from 4-nitoaniline and3,5-dimethylphenol were synthesized. Characterization of these compounds has been done on the basis of elemental analysis,electronic data, FT-IR,UV-Vis and 1 HNMR, as well as magnetic susceptibility and conductivity measurements. The nature of thecomplexes formed were studies following the mole ratio and continuous variation methods, Beer ' s law obeyed over a concentrationrange (1x10 -4 - 3x10 -4 M). High molar absorbtivity of the complex solutions were observed. From the analytical data, thestoichiomerty of the complexes has been found to be 1:2 (Metal:ligand). On the basis of physicochemical data tetrahedral

... Show More
Preview PDF
Publication Date
Sun Nov 01 2020
Journal Name
Journal Of Engineering
Convolutional Multi-Spike Neural Network as Intelligent System Prediction for Control Systems
...Show More Authors

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

... Show More
View Publication Preview PDF
Crossref (1)
Crossref
Publication Date
Mon Sep 30 2013
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Optimal Design of Cylinderical Ectrode Using Neural Network Modeling for Electrochemical Finishing
...Show More Authors

The finishing operation of the electrochemical finishing technology (ECF) for tube of steel was investigated In this study. Experimental procedures included qualitative
and quantitative analyses for surface roughness and material removal. Qualitative analyses utilized finishing optimization of a specific specimen in various design and operating conditions; value of gap from 0.2 to 10mm, flow rate of electrolytes from 5 to 15liter/min, finishing time from 1 to 4min and the applied voltage from 6 to 12v, to find out the value of surface roughness and material removal at each electrochemical state. From the measured material removal for each process state was used to verify the relationship with finishing time of work piece. Electrochemi

... Show More
View Publication Preview PDF
Publication Date
Sun Sep 30 2012
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Development of PVT Correlation for Iraqi Crude Oils Using Artificial Neural Network
...Show More Authors

Several correlations have been proposed for bubble point pressure, however, the correlations could not predict bubble point pressure accurately over the wide range of operating conditions. This study presents Artificial Neural Network (ANN) model for predicting the bubble point pressure especially for oil fields in Iraq. The most affecting parameters were used as the input layer to the network. Those were reservoir temperature, oil gravity, solution gas-oil ratio and gas relative density. The model was developed using 104 real data points collected from Iraqi reservoirs. The data was divided into two groups: the first was used to train the ANN model, and the second was used to test the model to evaluate their accuracy and trend stability

... Show More
View Publication Preview PDF
Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
PDCNN: FRAMEWORK for Potato Diseases Classification Based on Feed Foreword Neural Network
...Show More Authors

         The economy is exceptionally reliant on agricultural productivity. Therefore, in domain of agriculture, plant infection discovery is a vital job because it gives promising advance towards the development of agricultural production. In this work, a framework for potato diseases classification based on feed foreword neural network is proposed. The objective of this work  is presenting a system that can detect and classify four kinds of potato tubers diseases; black dot, common scab, potato virus Y and early blight based on their images. The presented PDCNN framework comprises three levels: the pre-processing is first level, which is based on K-means clustering algorithm to detect the infected area from potato image. The s

... Show More
View Publication Preview PDF
Scopus (9)
Crossref (1)
Scopus Clarivate Crossref
Publication Date
Thu Dec 01 2022
Journal Name
Iraqi Journal Of Science
PLAGIARISM DETECTION SYSTEM IN SCIENTIFIC PUBLICATION USING LSTM NETWORKS
...Show More Authors

Scopus (3)
Scopus
Publication Date
Tue Jul 31 2018
Journal Name
The Open Electrical & Electronic Engineering Journal
Minimum Delay Congestion Control in Differentiated Service Communication Networks
...Show More Authors

This paper presents a minimum delay congestion control in differentiated Service communication networks. The premium and ordinary passage services based fluid flow theory is used to build the suggested structure in high efficient manage. The established system is capable to adeptly manage both the physical network resource limitations and indefinite time delay related to networking system structure.

... Show More
View Publication
Scopus (1)
Crossref (2)
Scopus Crossref