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A Novel Invasive Weed Optimization Algorithm (IWO) by Whale Optimization Algorithm(WOA) to solve Large Scale Optimization Problems
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Abstract  

  In this work, two algorithms of Metaheuristic algorithms were hybridized. The first is Invasive Weed Optimization algorithm (IWO) it is a numerical stochastic optimization algorithm and the second is Whale Optimization Algorithm (WOA) it is an algorithm based on the intelligence of swarms and community intelligence. Invasive Weed Optimization Algorithm (IWO) is an algorithm inspired by nature and specifically from the colonizing weeds behavior of weeds, first proposed in 2006 by Mehrabian and Lucas. Due to their strength and adaptability, weeds pose a serious threat to cultivated plants, making them a threat to the cultivation process. The behavior of these weeds has been simulated and used in Invasive Weed Optimization Algorithm (IWO), as for the Whale Optimization Algorithm (WOA) uses the intelligence of the swarms to reach the goal and achieve the best solution, which simulates the unique hunting behavior of humpback whales, which is called fishing by bubble trap hunting by creating distinctive bubbles along a circle or a path in the form of 9 has appeared for the first time in 2016 by Mirjalili and Lewis. In order to benefit from the intelligence of the flocks and to avoid falling into local solutions, the new hybridization between the IWO and WOA algorithm was proposed to launch the new hybrid algorithm (IWOWOA). The new hybrid algorithm (IWOWOA) was applied on 23 functions of large scale optimization problems, The proposed algorithm showed very high efficiency in solving these functions. The proposed algorithm was able to reach the optimal solutions by achieving the minimum value of most of these functions. This algorithm was compared with the basic algorithms IWO, WOA and two algorithms that follow the swarm system these algorithms are particle swarm optimization (PSO) and chicken swarm optimization (CSO) [7], they have been statistically tested by calculating the mean arithmetic μ and standard deviation σ for these functions.

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Publication Date
Sun Jun 08 2025
Journal Name
International Journal Of Data And Network Science
Multi-objective of wind-driven optimization as feature selection and clustering to enhance text clustering
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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

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Publication Date
Fri Nov 24 2023
Journal Name
International Journal Of Statistics In Medical Research
A Novel Algorithm for Predicting Antimicrobial Resistance in Unequal Groups of Bacterial Isolates
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Choosing antimicrobials is a common dilemma when the expected rate of bacterial resistance is high. The observed resistance values in unequal groups of isolates tested for different antimicrobials can be misleading. This can affect the decision to recommend one antibiotic over the other. We analyzed recalled data with the statistical consideration of unequal sample groups. Data was collected concerning children suspected to have typhoid fever at Al Alwyia Pediatric Teaching Hospital in Baghdad, Iraq. The study period extended from September 2021 to September 2022. A novel algorithm was developed to compare the drug sensitivity among unequal numbers of Salmonella typhi (S. Typhi) isolates tested with different antibacterials.

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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)
Formulation and Optimization of Oral Fast Dissolving Prochloperazine Maleate Tablets
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Prochloperazine maleate (PCM) is one of the most prescribed phenothiazine. The purpose of the present research was to develop fast dissolving tablets of PCM with β-cyclodextrin inclusion complex. Tablets prepared  by wet granulation with sublimation and by using  different superdisintegrants type [ low-hydroxypropylcellulose LH21 (L-HPC LH21), carboxymethylcellulose calcium (ECG505), crospovidone (CP)], and different type of subliming agents (urea and ammonium bicarbonate (AB)). Tablets evaluated for its % friability, disintegration time, wetting time, hardness, content uniformity, weight variation, in vitro dissolution studies. For further enhancement of disintegration and dissolution, PCM orodispersible tablet were formula

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Publication Date
Wed May 15 2024
Journal Name
Al-rafidain Journal Of Medical Sciences ( Issn 2789-3219 )
Preparation and Optimization of Olanzapine as Transdermal Nanoparticles Delivery System
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Background: The treatment of schizophrenia typically involves the use of olanzapine (OLZ), a typical antipsychotic drug that has poor oral bioavailability due to its low solubility and first-pass effect.  Objective: To prepare and optimize OLZ as nanoparticles for transdermal delivery to avoid problems with oral administration. Methods: The nanoprecipitation technique was applied for the preparation of eight OLZ nanoparticles by using different polymers with various ratios. Nanoparticles were evaluated using different methods, including particle size, polydispersity index (PDI), entrapment efficiency (EE%), zeta potential and an in vitro release study. The morphology was evaluated by a field emission scanning electron microscope (F

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Publication Date
Mon Apr 24 2017
Journal Name
Spe Kingdom Of Saudi Arabia Annual Technical Symposium And Exhibition
Optimization of Infill Drilling in Whicher Range Field in Australia
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Abstract<p>Now that most of the conventional reservoirs are being depleted at a rapid pace, the focus is on unconventional reservoirs like tight gas reservoirs. Due to the heterogeneous nature and low permeability of unconventional reservoirs, they require a huge number of wells to hit all the isolated hydrocarbon zones. Infill drilling is one of the most common and effective methods of increasing the recovery, by reducing the well spacing and increasing the sweep efficiency. However, the problem with drilling such a large number of wells is the determination of the optimum location for each well that ensures minimum interference between wells, and accelerates the recovery from the field. Detail</p> ... Show More
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Publication Date
Sat Jan 01 2022
Journal Name
International Journal Of Mechanical Engineering
Process Parameters Optimization in Single Point Incremental Forming Of Al1050
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This work aims to optimize surface roughness, wall angle deviation, and average wall thickness as output responses of ALuminium-1050 alloy cone formed by the single point incremental sheet metal forming process. The experiments are accomplished based on the use of a mixed level Taguchi experimental design with an L18 orthogonal array. Six levels of step depth, three levels of tool diameter, feed rate, and tool rotational speed have been considered as input process parameters. The analyses of variance (ANOVA) have been used to investigate the significance of parameters and the effect of their levels for minimum surface roughness, minimum wall angle deviation, and maximum average wall thickness. The results indicate that step depth and tool r

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Publication Date
Sat Jan 01 2022
Journal Name
Latin American Journal Of Solids And Structures
Peak Ground Acceleration Models Predictions Utilizing Two Metaheuristic Optimization Techniques
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Publication Date
Thu Oct 01 2015
Journal Name
Engineering And Technology Journal
Genetic Based Optimization Models for Enhancing Multi- Document Text Summarization
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Publication Date
Sat Jan 01 2022
Journal Name
Latin American Journal Of Solids And Structures
Peak Ground Acceleration Models Predictions Utilizing Two Metaheuristic Optimization Techniques
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Publication Date
Tue Feb 01 2022
Journal Name
Baghdad Science Journal
Retina Based Glowworm Swarm Optimization for Random Cryptographic Key Generation
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The biometric-based keys generation represents the utilization of the extracted features from the human anatomical (physiological) traits like a fingerprint, retina, etc. or behavioral traits like a signature. The retina biometric has inherent robustness, therefore, it is capable of generating random keys with a higher security level compared to the other biometric traits. In this paper, an effective system to generate secure, robust and unique random keys based on retina features has been proposed for cryptographic applications. The retina features are extracted by using the algorithm of glowworm swarm optimization (GSO) that provides promising results through the experiments using the standard retina databases. Additionally, in order t

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