Peak Ground Acceleration Models Predictions Utilizing Two Metaheuristic Optimization Techniques
(15)
(15)
Publication Date
Fri Feb 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of classical method and optimization methods for estimating parameters in nonlinear ordinary differential equation
المعادلات التفاضلية العادية اللاخطية
الشريحة الجزائية
الانحدار اللامعلمي
الانحدار شبه المعلمي
خوارزمية التطور التفاضلي .
Nonlinear Ordinary Differential Equations
penalized spline
Nonparametric Regression
Semi-Parametric Regression
differential evolution algorithm
ABSTRICT:
This study is concerned with the estimation of constant and time-varying parameters in non-linear ordinary differential equations, which do not have analytical solutions. The estimation is done in a multi-stage method where constant and time-varying parameters are estimated in a straight sequential way from several stages. In the first stage, the model of the differential equations is converted to a regression model that includes the state variables with their derivatives and then the estimation of the state variables and their derivatives in a penalized splines method and compensating the estimations in the regression model. In the second stage, the pseudo- least squares method was used to es
... Show More
Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
On semi strongly (E, F)-convex functions and semi strongly (E, F)-convex optimization problems
Abstract<p>In this paper, a new class of non-convex functions called semi strongly (<italic>E, F</italic>)-convex functions are presented. This class represents a natural extension of semi strongly <italic>E</italic>-convex functions shown in the literature. Different properties of this class of functions are discussed. Optimality properties of constrained optimization problems in which the objective function or the inequality constraints functions are semi strongly (<italic>E, F</italic>)-convex are proved for this class.</p>
(3)
(1)
Publication Date
Thu Oct 26 2017
Journal Name
International Journal Of Pure And Applied Mathematics
ON CONVEX FUNCTIONS, $E$-CONVEX FUNCTIONS AND THEIR GENERALIZATIONS: APPLICATIONS TO NON-LINEAR OPTIMIZATION PROBLEMS
Contents IJPAM: Volume 116, No. 3 (2017)
Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
Optimization of Voltammetric Determination of Dysprosium (III) Using Plackett-Burman and RSM-CCD Experimental Designs
Dysprosium
Experimental Designs
Optimization
Rare Earth Elements
Voltammetry.
This study was aimed to develop an optimized Dy determination method using differential pulse voltammetry (DPV). The Plackett-Burman (PB) experimental design was used to select significant factors that affect the electrical current response, which were further optimized using the response surface method-central composite design (RSM-CCD). The type of electrolyte solution and amplitude modulation were found as two most significant factors, among the nine factors tested, which enhance the current response based on PB design. Further optimization using RSM-CCD shows that the optimum values for the tw
... Show More
(7)
(3)
Publication Date
Tue Sep 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Adsorption Optimization of Congo Red Dye onto Electrospun
Nanofibers of Polyacrylonitrile functionalized with Fe3O4
Nanoparticles
Adsorption
Congo red
Nanofibers
Electrospining
Polyacrylonitrile
Ferric oxidenanoparticles
Desorption.
Ferric oxide nanoparticles Fe3O4NPs have been prepared by the coprecipitation method, which were used to functionalize the surface of electrospun nanofibers of polyacrylonitrile to increase their effectiveness in adsorption of Congo red (CR) dye from their aqueous solutions. The effect factors of adsorption were systematically investigated such as adsorbent mass, initial concentration, contact time, temperature, ionic strength and pH. The maximum adsorbed amount of the dye was at 0.003g of adsorbent. The adsorption of dye increased with increasing initial dye concentration and the system reaches to the equilibrium state at 150 min. The adsorbed dye capacity decreases with increasing temperature which indicates to the exothermic nature of ad
... Show MorePublication Date
Mon Mar 09 2026
Journal Name
International Journal Of Data And Network Science
Multi-objective of wind-driven optimization as feature selection and clustering to enhance text clustering
Text Clustering
Multi-Objectives
Wind Driven Optimization
K-Means
Unsupervised Feature Selection
Meta-heuristics optimization
Text Clustering consists of grouping objects of similar categories. The initial centroids influence operation of the system with the potential to become trapped in local optima. The second issue pertains to the impact of a huge number of features on the determination of optimal initial centroids. The problem of dimensionality may be reduced by feature selection. Therefore, Wind Driven Optimization (WDO) was employed as Feature Selection to reduce the unimportant words from the text. In addition, the current study has integrated a novel clustering optimization technique called the WDO (Wasp Swarm Optimization) to effectively determine the most suitable initial centroids. The result showed the new meta-heuristic which is WDO was employed as t
... Show More
(1)
Publication Date
Sun Jan 19 2014
Journal Name
Romanian Biotechnological Letters
Publication Date
Tue Nov 09 2021
Journal Name
Abu Dhabi International Petroleum Exhibition & Conference
Numerical Simulation of Gas Lift Optimization Using Artificial Intelligence for a Middle Eastern Oil Field
Abstract<p>Artificial lift techniques are a highly effective solution to aid the deterioration of the production especially for mature oil fields, gas lift is one of the oldest and most applied artificial lift methods especially for large oil fields, the gas that is required for injection is quite scarce and expensive resource, optimally allocating the injection rate in each well is a high importance task and not easily applicable. Conventional methods faced some major problems in solving this problem in a network with large number of wells, multi-constrains, multi-objectives, and limited amount of gas. This paper focuses on utilizing the Genetic Algorithm (GA) as a gas lift optimization algorit</p>
... Show More
evolutionary algorithm
gas lift
artificial intelligence
upstream oil & gas
machine learning
optimization problem
correlation
presented
allocation
reservoir pressure
(8)
(5)
Publication Date
Mon Jan 01 2018
Journal Name
Journal Of Engineering
Publication Date
Tue Dec 05 2017
Journal Name
International Journal Of Science And Research (ijsr)
(1)