Preferred Language
Articles
/
M-bvH5wBmraWrQ4d5kdk
Modified Optimization Algorithms for Infinite Integro-Differential Equations via Generalized Laguerre Polynomials
...Show More Authors

This study emphasizes the infinite-boundary integro-differential equation. To examine the approximate solution of the problem, two modified optimization algorithms are proposed based on generalized Laguerre functions. In the first technique, the proposed method is applied to the original problem by approximating the solution using the truncated generalized Laguerre polynomial of the unknown function, optimizing coefficients through error minimization, and transforming the integro-differential equation into an algebraic equation. In contrast, the second approach incorporates a penalty term into the objective function to effectively enforce boundary and integral constraints. This technique reduces the original problem to a mathematical optimization problem, making it easier to manage. The proposed methods are examined through various experiments, including numerical applications such as thermal, pharmacokinetic, oscillatory, aerodynamic, and ecological models, to demonstrate the validity, efficiency, and applicability of the techniques. Error analysis indicates that the approximation becomes more accurate as the number of generalized Laguerre basis functions increases.

Scopus Crossref
View Publication
Publication Date
Tue Jan 01 2019
Journal Name
International Journal Of Civil Engineering And Technology
Generalized tupled common fixed point theorems for weakly compatible mappings in fuzzy metric space
...Show More Authors

Scopus (11)
Scopus
Publication Date
Sun Dec 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Use Generalized Pareto Survival Models to Estimation Optimal Survival Time for Myocardial Infarction Patients
...Show More Authors

The survival analysis is one of the modern methods of analysis that is based on the fact that the dependent variable represents time until the event concerned in the study. There are many survival models that deal with the impact of explanatory factors on the likelihood of survival, including the models proposed by the world, David Cox, one of the most important and common models of survival, where it consists of two functions, one of which is a parametric function that does not depend on the survival time and the other a nonparametric function that depends on times of survival, which the Cox model is defined as a semi parametric model, The set of parametric models that depend on the time-to-event distribution parameters such as

... Show More
View Publication Preview PDF
Crossref
Publication Date
Mon Feb 05 2052
Journal Name
Partial Differential Equations In Applied Mathematics
A hybrid analytical method for fractional order Klein–Gordon and Burgers equations
...Show More Authors

Scopus (2)
Scopus
Publication Date
Sat Apr 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Application the generalized estimating equation Method (GEE) to estimate of conditional logistic regression model for repeated measurements
...Show More Authors

Conditional logistic regression is often used to study the relationship between event outcomes and specific prognostic factors in order to application of logistic regression and utilizing its predictive capabilities into environmental studies. This research seeks to demonstrate a novel approach of implementing conditional logistic regression in environmental research through inference methods predicated on longitudinal data. Thus, statistical analysis of longitudinal data requires methods that can properly take into account the interdependence within-subjects for the response measurements. If this correlation ignored then inferences such as statistical tests and confidence intervals can be invalid largely.

... Show More
View Publication Preview PDF
Crossref
Publication Date
Sat Dec 01 2012
Journal Name
International Journal Of Contemporary Mathematical Sciences
Approximation by Convex Polynomials in Weighted Spaces
...Show More Authors

Here, we found an estimation of best approximation of unbounded functions which satisfied weighted Lipschitz condition with respect to convex polynomial by means of weighted Totik-Ditzian modulus of continuity

Publication Date
Wed Jan 01 2020
Journal Name
Cogent Engineering
On the computational aspects of Charlier polynomials
...Show More Authors

View Publication
Scopus (39)
Crossref (36)
Scopus Clarivate Crossref
Publication Date
Thu Dec 31 2015
Journal Name
Al-khwarizmi Engineering Journal
Prediction of Performance Equations for Household Compressors Depending on Manufacturing Data for Refrigerators and Freezers
...Show More Authors

Abstract

 A surface fitting model is developed based on calorimeter data for two famous brands of household compressors. Correlation equations of ten coefficient polynomials were found as a function of refrigerant saturating and evaporating temperatures in range of (-35℃ to -10℃) using Matlab software for cooling capacity, power consumption, and refrigerant mass flow rate.

Additional correlations equations for these variables as a quick choice selection for a proper compressor use at ASHRAE standard that cover a range of swept volume range (2.24-11.15) cm3.

The result indicated that these surface fitting models are accurate with in ± 15% for 72 compressors model of cooling cap

... Show More
View Publication Preview PDF
Publication Date
Tue Jun 30 2026
Journal Name
Journal Of Economics And Administrative Sciences
Nonparametric Control Charts Estimation Using Hybrid Cyber-Intelligence Algorithms for Stock Market Monitoring
...Show More Authors

This paper introduces a novel nonparametric hybrid cyber-intelligence-based statistical process control and anomaly detection framework in time series data. It is developed to overcome the shortcomings of the classical control schemes in dealing with complex, abnormal, and noisy input data, especially when it is autocorrelated. The proposed methodology combines three technical pillars: First, it utilizes a bidirectional long-short-term memory architecture (Bi-LSTM) to capture long-term time dependency and learn nonlinear patterns, leaving only true deviations as residuals that remove trends and noises from the market. Second, it adopts the Golden Eagle Optimizer (GEO) algorithm for optimal parameter selection. This intelligent algor

... Show More
View Publication
Crossref
Publication Date
Sun Mar 04 2018
Journal Name
Baghdad Science Journal
An Approximate Solution of some Variational Problems Using Boubaker Polynomials
...Show More Authors

In this paper, an approximate solution of nonlinear two points boundary variational problem is presented. Boubaker polynomials have been utilized to reduce these problems into quadratic programming problem. The convergence of this polynomial has been verified; also different numerical examples were given to show the applicability and validity of this method.

View Publication Preview PDF
Scopus (4)
Scopus Clarivate Crossref
Publication Date
Fri Jan 01 2016
Journal Name
Journal Of Engineering
Improve the Performance of PID Controller by Two Algorithms for Controlling the DC Servo Motor
...Show More Authors

The paper uses the Direct Synthesis (DS) method for tuning the Proportional Integral Derivative (PID) controller for controlling the DC servo motor. Two algorithms are presented for enhancing the performance of the suggested PID controller. These algorithms are Back-Propagation Neural Network and Particle Swarm Optimization (PSO). The performance and characteristics of DC servo motor are explained. The simulation results that obtained by using Matlab program show that the steady state error is eliminated with shorter adjusted time when using these algorithms with PID controller. A comparative between the two algorithms are described in this paper to show their effectiveness, which is found that the PSO algorithm gives be

... Show More
View Publication Preview PDF