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Enhanced zebra optimization algorithm for sustainable combined economic and emission dispatch in power systems
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The Combined Economic Emission Dispatch (CEED) problem is crucial for optimizing power system operation by minimizing costs and emissions while ensuring grid stability and meeting demand. This paper addresses the complex, nonlinear, and nonconvex nature of CEED, arising from factors like valve-point effects and transmission losses, which necessitates efficient metaheuristic algorithms. We introduce an Improved Zebra Optimization Algorithm (IMZOA), an enhanced bio-inspired technique integrating advanced adaptive foraging and dynamic defense mechanisms, along with a cubic function for CEED modeling, to improve search efficiency and convergence. IMZOA demonstrates significant numerical improvements, achieving up to a 0.80 % cost reduction for the six-unit system compared to the standard Zebra Optimization Algorithm (ZOA), minimizing hourly fuel cost to $69,563.04 for the Iraqi system, and exhibiting competitive performances with a fuel cost of $197,974.2047 per hour for the 110-unit system. IMZOA's effectiveness is validated on three benchmark systems: a six-unit IEEE test system, the 31-unit Iraqi power generation system, and a large-scale 110-unit system. Experimental results show that IMZOA significantly reduces costs and emissions compared to established algorithms like LM and SA, and improved methods such as asinhCAOA, RLADE, and the standard Zebra Optimization Algorithm ZOA. Specifically, for the six-unit system, IMZOA also showed superior environmental performance. For the Iraqi system, IMZOA outperformed PSO and other state-of-the-art approaches. Moreover, for the 110-unit system, IMZOA demonstrated competitive performance comparable to advanced algorithms like EBWO and ESNS, while maintaining lower standard deviations, indicating greater solution stability. These results underscore IMZOA's robustness and efficiency for small, medium, and large-scale CEED problems, making it a promising solution for cost-effective and environmentally sustainable power dispatch.

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Publication Date
Tue Mar 28 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Response Surface Methodology for Development and Optimization of Theophylline Pulmonary Delivery System
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The aim of the present study was to develop theophylline (TP) inhalable sustained delivery system by preparing solid lipid microparticles using glyceryl behenate (GB) and poloxamer 188 (PX) as a lipid carrier and a surfactant respectively. The method involves loading TP nanoparticles into the lipid using high shear homogenization – ultrasonication technique followed by lyophilization. The compositional variations and interactions were evaluated using response surface methodology, a Box – Behnken design of experiment (DOE). The DOE constructed using TP (X1), GB (X2) and PX (X3) levels as independent factors. Responses measured were the entrapment efficiency (% EE) (Y1), mass median

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Publication Date
Sun Jul 01 1990
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
MEDIUM OPTIMIZATION FOR BIOMASS PRODUCTION AND PROTEIN CONTENT OF CANDIDA UTILES K50
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Molasse medium containing different concentrations of (NH4)2 SO4, (NH4)3 PO4, urea, KCI, and P2O5 were compared with the medium used for commercial production of C. utilis in a factory south of Iraq. An efficient medium, which produced 19. 16% dry wt. and 5. 78% protein, was developed. The effect of adding various concentrations of micronutrients (FeSO4, 7T20, MnSO4. 7H20, ZnSO4. 7E20) was also studied. Results showed that FeSo4. 7H20 caused a noticeable increase in both dry wt. and protein content of the yeast.

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Publication Date
Tue Jul 01 2025
Journal Name
South African Journal Of Chemical Engineering
Electrocoagulation process for cobalt removal from industrial wastewater: Optimization and kinetic study
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Publication Date
Thu Sep 08 2022
Journal Name
Al-khwarizmi Engineering Journal
Performance Prediction in EDM Process for Al 6061 Alloy Using Response Surface Methodology and Genetic Algorithm
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The Electric Discharge (EDM) method is a novel thermoelectric manufacturing technique in which materials are removed by a controlled spark erosion process between two electrodes immersed in a dielectric medium. Because of the difficulties of EDM, determining the optimum cutting parameters to improve cutting performance is extremely tough. As a result, optimizing operating parameters is a critical processing step, particularly for non-traditional machining process like EDM. Adequate selection of processing parameters for the EDM process does not provide ideal conditions, due to the unpredictable processing time required for a given function. Models of Multiple Regression and Genetic Algorithm are considered as effective methods for determ

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Publication Date
Sat Jun 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
"Analyzing of the economic relationship between Dutch disease and the disruption of the Iraq economic structure "
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The status of the semi total stoppage and non-use and waste of economic made studying and analyzing Dutch disease of high importance because it is a major cause in aggravation of this status which happened to the Iraqi economy in almost complete way and the relative big importance that oil source has and its domination on the largest percentage in the gross domestic product and exports that Iraqi economy is relying largely in funding the national budget made the concentration of the study on this subject an important and necessary within the important economic events that Iraqi economy witnessed after 2003 till 2016 to give a clear and an overall picture of the reality of the unilateral Iraqi economy under the status of semi tota

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Publication Date
Fri Jan 31 2025
Journal Name
Passer Journal Of Basic And Applied Sciences
Enhanced Security Taxonomy for Fog-Enabled VANETs: A Comprehensive Survey on Attacks, Challenges, Applications and Architectures
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Vehicular Ad Hoc Networks (VANETs) are integral to Intelligent Transportation Systems (ITS), enabling real-time communication between vehicles and infrastructure to enhance traffic flow, road safety, and passenger experience. However, the open and dynamic nature of VANETs presents significant privacy and security challenges, including data eavesdropping, message manipulation, and unauthorized access. This study addresses these concerns by leveraging advancements in Fog Computing (FC), which offers lowlatency, distributed data processing near-end devices to enhance the resilience and security of VANET communications. The paper comprehensively analyzes the security frameworks for fog-enabled VANETs, introducing a novel taxonomy that c

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Publication Date
Tue Oct 01 2024
Journal Name
Results In Engineering
Nanomaterials in asphalt cement: exploring their single and combined effects on the physical and rheological properties
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Publication Date
Wed Oct 30 2019
Journal Name
Cambridge Scholars Publishing.
Intelligent systems in building;
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Publication Date
Mon Feb 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Fuzzy logic in the estimate of reliability function for k - components systems
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Abstract:

One of the important things provided by fuzzy model is to identify the membership functions. In the fuzzy reliability applications with failure functions of the kind who cares that deals with positive variables .There are many types of membership functions studied by many researchers, including triangular membership function, trapezoidal membership function and bell-shaped membership function. In I research we used beta function. Based on this paper study classical method to obtain estimation fuzzy reliability function for both series and parallel systems.

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Publication Date
Fri Apr 01 2022
Journal Name
Baghdad Science Journal
Improved Firefly Algorithm with Variable Neighborhood Search for Data Clustering
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Among the metaheuristic algorithms, population-based algorithms are an explorative search algorithm superior to the local search algorithm in terms of exploring the search space to find globally optimal solutions. However, the primary downside of such algorithms is their low exploitative capability, which prevents the expansion of the search space neighborhood for more optimal solutions. The firefly algorithm (FA) is a population-based algorithm that has been widely used in clustering problems. However, FA is limited in terms of its premature convergence when no neighborhood search strategies are employed to improve the quality of clustering solutions in the neighborhood region and exploring the global regions in the search space. On the

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