Preferred Language
Articles
/
joe-2034
Spatial Prediction of Monthly Precipitation in Sulaimani Governorate using Artificial Neural Network Models
...Show More Authors

ANN modeling is used here to predict missing monthly precipitation data in one station of the eight weather stations network in Sulaimani Governorate. Eight models were developed, one for each station as for prediction. The accuracy of prediction obtain is excellent with correlation coefficients between the predicted and the measured values of monthly precipitation ranged from (90% to 97.2%). The eight ANN models are found after many trials for each station and those with the highest correlation coefficient were selected. All the ANN models are found to have a hyperbolic tangent and identity activation functions for the hidden and output layers respectively, with learning rate of (0.4) and momentum term of (0.9), but with different data set sub-division into training, testing and holdout data sub-sets, and different number of hidden nodes in the hidden layer. It is found that it is not necessary that the nearest station to the station under prediction has the highest effect; this may be attributed to the high differences in elevation between the stations. It can also found that the variance is not necessary has effect on the correlation coefficient obtained.

Crossref
View Publication Preview PDF
Quick Preview PDF
Publication Date
Fri Jul 07 2017
Journal Name
International Journal Of Science And Research (ijsr)
Automatic brain tumor segmentation from MRI Images using superpixels based split and Merge algorithm
...Show More Authors

RA Ali, LK Abood, Int J Sci Res, 2017 - Cited by 2

View Publication
Publication Date
Sat Dec 31 2022
Journal Name
International Journal Of Intelligent Engineering And Systems
Using Three-Dimensional Logistic Equations and Glowworm Swarm Optimization Algorithm to Generate S-Box
...Show More Authors

View Publication
Scopus (4)
Crossref (1)
Scopus Crossref
Publication Date
Mon Dec 30 2019
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Biodiesel production from used vegetable oil (sunflower cooking oil) using eggshell as bio catalyst
...Show More Authors

Bio-diesel is an attractive fuel fordiesel engines. The feedstock for bio-diesel production is usually vegetable oil, waste cooking oil, or animal fats. This work provides an overview concerning bio-diesel production. Also, this work focuses on the commercial production of biodiesel. The objective is to study the influence of these parameters on the yield of produced. The biodiesel production affecting by many parameters such s alcohol ratio (5%, 10%,15 %, 20%,25%,30%35% vol.), catalyst loading (5,10,15,20,25) g,temperature (45,50,55,60,65,70,75)°C,reaction time (0-6) h, mixing rate (400-1000) rpm. the maximum bio-diesel production yield (95%) was obtained using 20% methanol ratio and 15g biocatalyst at 60°C.

View Publication Preview PDF
Crossref (2)
Crossref
Publication Date
Sat Dec 01 2018
Journal Name
Digital Signal Processing
Reverberant signal separation using optimized complex sparse nonnegative tensor deconvolution on spectral covariance matrix
...Show More Authors

View Publication
Scopus (9)
Crossref (6)
Scopus Clarivate Crossref
Publication Date
Wed Dec 27 2017
Journal Name
Al-khwarizmi Engineering Journal
A New Structure for Cascaded Single-Stage Distributed Amplifier Using Proposed Active Inductor Loads
...Show More Authors

A modification to cascaded single-stage distributed amplifier (CSSDA) design by using active inductor is proposed. This modification is shown to render the amplifier suitable for high gain operation in small on-chip area. Microwave office program simulation of the Novel design approach shows that it has performance compatible with the conventional distributed amplifiers but with smaller area. The CSSDA is suitable for optical and satellite communication systems.

View Publication Preview PDF
Publication Date
Sun Sep 07 2014
Journal Name
Baghdad Science Journal
Deriving the Composite Simpson Rule by Using Bernstein Polynomials for Solving Volterra Integral Equations
...Show More Authors

In this paper we use Bernstein polynomials for deriving the modified Simpson's 3/8 , and the composite modified Simpson's 3/8 to solve one dimensional linear Volterra integral equations of the second kind , and we find that the solution computed by this procedure is very close to exact solution.

View Publication Preview PDF
Crossref (2)
Crossref
Publication Date
Tue Aug 01 2023
Journal Name
Advances In Mechanical Engineering
Using a spherical inverted pendulum and statokinesigram for modeling and evaluating quiet standing posture
...Show More Authors

This paper proposes a new approach to model and analyze erect posture, based on a spherical inverted pendulum which is used to mimic the body posture. The pendulum oscillates in two directions, [Formula: see text] and [Formula: see text], from which the mathematical model was derived and two torque components in oscillation directions were introduced. They are estimated using stabilometric data acquired by a foot pressure mapping system. The model was quantitatively investigated using data from 19 participants, who were first were classified into three groups, according to the foot arch-index. Stabilometric data were then collected and fed into the model to estimate the torque’s components. The components were statistically proce

... Show More
View Publication
Scopus (2)
Crossref (2)
Scopus Clarivate Crossref
Publication Date
Tue Jun 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Comparison Between Partial Least Square Regression(PLSR) and Tree Regression by Using Simulation(RT).
...Show More Authors

This research discussed, the process of comparison between the regression model of partial least squares and tree regression, where these models included two types of statistical methods represented by the first type "parameter statistics" of the partial least squares, which is adopted when the number of variables is greater than the number of observations and also when the number of observations larger than the number of variables, the second type is the "nonparametric statistic" represented by tree regression, which is the division of data in a hierarchical way. The regression models for the two models were estimated, and then the comparison between them, where the comparison between these methods was according to a Mean Square

... Show More
View Publication Preview PDF
Crossref
Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Bayesian Tobit Quantile Regression Model Using Double Adaptive elastic net and Adaptive Ridge Regression
...Show More Authors

     Recently Tobit  Quantile Regression(TQR) has emerged as an important tool in statistical analysis . in order to improve the parameter estimation in (TQR) we proposed Bayesian hierarchical model with double adaptive elastic net technique  and Bayesian hierarchical model with adaptive ridge regression technique .

 in double adaptive elastic net technique we assume  different penalization parameters  for penalization different regression coefficients in both parameters λ1and  λ, also in adaptive ridge regression technique we assume different  penalization parameters for penalization different regression coefficients i

... Show More
View Publication Preview PDF
Crossref
Publication Date
Wed Apr 01 2020
Journal Name
Plant Archives
Land cover change detection using satellite images based on modified spectral angle mapper method
...Show More Authors

This research depends on the relationship between the reflected spectrum, the nature of each target, area and the percentage of its presence with other targets in the unity of the target area. The changes occur in Land cover have been detected for different years using satellite images based on the Modified Spectral Angle Mapper (MSAM) processing, where Landsat satellite images are utilized using two software programming (MATLAB 7.11 and ERDAS imagine 2014). The proposed supervised classification method (MSAM) using a MATLAB program with supervised classification method (Maximum likelihood Classifier) by ERDAS imagine have been used to get farthest precise results and detect environmental changes for periods. Despite using two classificatio

... Show More
Scopus (3)
Scopus