Preferred Language
Articles
/
jih-1811
Using Approximation Non-Bayesian Computation with Fuzzy Data to Estimation Inverse Weibull Parameters and Reliability Function
...Show More Authors

        In real situations all observations and measurements are not exact numbers but more or less non-exact, also called fuzzy. So, in this paper, we use approximate non-Bayesian computational methods to estimate inverse Weibull parameters and reliability function with fuzzy data. The maximum likelihood and moment estimations are obtained as non-Bayesian estimation. The maximum likelihood estimators have been derived numerically based on two iterative techniques namely “Newton-Raphson” and the “Expectation-Maximization” techniques. In addition, we provide compared numerically through Monte-Carlo simulation study to obtained estimates of the parameters and reliability function in terms of their mean squared error values and integrated mean squared error values respectively.

Crossref
View Publication Preview PDF
Quick Preview PDF
Publication Date
Thu Jun 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Bayes Analysis for the Scale Parameter of Gompertz Distribution
...Show More Authors

In this paper, we investigate the behavior of the bayes estimators, for the scale parameter of the Gompertz distribution under two different loss functions such as, the squared error loss function, the exponential loss function (proposed), based different double prior distributions represented as erlang with inverse levy prior, erlang with non-informative prior, inverse levy with non-informative prior and erlang with chi-square prior.

The simulation method was fulfilled to obtain the results, including the estimated values and the mean square error (MSE) for the scale parameter of the Gompertz distribution, for different cases for the scale parameter of the Gompertz distr

... Show More
View Publication Preview PDF
Crossref
Publication Date
Wed Dec 01 2021
Journal Name
Journal Of Economics And Administrative Sciences
Mathematical Modelling of Gene Regulatory Networks
...Show More Authors

    This research includes the use of an artificial intelligence algorithm, which is one of the algorithms of biological systems which is the algorithm of genetic regulatory networks (GRNs), which is a dynamic system for a group of variables representing space within time. To construct this biological system, we use (ODEs) and to analyze the stationarity of the model we use Euler's method. And through the factors that affect the process of gene expression in terms of inhibition and activation of the transcription process on DNA, we will use TF transcription factors. The current research aims to use the latest methods of the artificial intelligence algorithm. To apply Gene Regulation Networks (GRNs), we used a progr

... Show More
View Publication Preview PDF
Crossref
Publication Date
Thu Aug 01 2019
Journal Name
International Journal Of Research - Granthaalayah
CALCULATION OF MULTIPLE MIXING RATIOS OF GAMMA RAYS FROM 𝑵𝒅(𝒏,𝒏)𝟔𝟎 𝟏𝟒𝟐−𝟏𝟓𝟎 ) 𝟔𝟎𝑵𝒅 𝟏𝟒𝟐−𝟏𝟓𝟎 INTERACTION
...Show More Authors

In the current research, multiple mixing ratios of gamma -transitions of the energy levels 60𝑁𝑑 142−150 isotopes populated in 𝑁𝑑(𝑛, 𝑛 ˊ 60 142−150 ) 60𝑁𝑑 142−150 interaction are calculated using the constant statistical tensor (CST) method. The results obtained are, in general, in good agreement or consistent, within the experimental error, with the results published in the previously researches. Existing discrepancies result from inaccuracies in the experimental results of previous works. The current results confirm the validity of the constant statistical tenser method of calculating the values of mixing ratios and its predictability of errors in experimental results

Publication Date
Sat Oct 01 2016
Journal Name
Journal Of Theoretical And Applied Information Technology
Factors affecting global virtual teams’ performance in software projects
...Show More Authors

Scopus (23)
Scopus