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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 the multi-objective first time as unsupervised Feature Selection (WDOFS) and the second time as a Clustering algorithm (WDOC). For example, the WDOC outperformed Harmony Search and Particle Swarm in terms of F-measurement by 93.3%; in contrast, text clustering's performance improves 0.9% because of using suggested clustering on the proposed feature selection. With WDOFS more than 50 percent of features have been removed from the other examination of features. The best result got the multi-objectives with F-measurement 98.3%.

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Publication Date
Wed Apr 01 2015
Journal Name
Journal Of Economics And Administrative Sciences
Multi-objectives probabilistic Aggregate production planning with practical application
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In this research, has been to building a multi objective Stochastic Aggregate Production Planning model for General al Mansour company Data with Stochastic  demand under changing of market and uncertainty environment in aim to draw strong production plans.  The analysis to derive insights on management issues regular and extra labour costs and the costs of maintaining inventories and good policy choice under the influence medium and optimistic adoption of the model of random has adoption form and had adopted two objective functions total cost function (the core) and income and function for a random template priority compared with fixed forms with objective function and the results showed that the model of two phases wit

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Publication Date
Thu Jun 19 2025
Journal Name
Vokasi Unesa Bulletin Of Engineering, Technology And Applied Science
Password Authentication Using Modify Multi-Connect Architecture Associative Memory
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Abstract: Password authentication is one of the mechanisms that are widely used to authenticate an authorized user. In this research proposed password authentication for both graphical and textual password by using new technique is Modify Multi-connect architecture (MMCA) algorithm for more efficient in speed and accuracy. Among 100 test the accuracy result is 100% for graphical and textual password to authenticate a user, and the process time to authenticate each user is 0.5 and 1 seconds for textual password and graphical password respectively.

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Publication Date
Wed Feb 16 2022
Journal Name
Journal Of Economics And Administrative Sciences
Solving Resource Allocation Model by Using Dynamic Optimization Technique for Al-Raji Group Companies for Soft Drinks and Juices
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In this paper, the problem of resource allocation at Al-Raji Company for soft drinks and juices was studied. The company produces several types of tasks to produce juices and soft drinks, which need machines to accomplish these tasks, as it has 6 machines that want to allocate to 4 different tasks to accomplish these tasks. The machines assigned to each task are subject to failure, as these machines are repaired to participate again in the production process. From past records of the company, the probability of failure machines at each task was calculated depending on company data information. Also, the time required for each machine to complete each task was recorded. The aim of this paper is to determine the minimum expected ti

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Publication Date
Sat Sep 30 2017
Journal Name
Al-khwarizmi Engineering Journal
Robot Arm Path Planning Using Modified Particle Swarm Optimization based on D* algorithm
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Abstract

Much attention has been paid for the use of robot arm in various applications. Therefore, the optimal path finding has a significant role to upgrade and guide the arm movement. The essential function of path planning is to create a path that satisfies the aims of motion including, averting obstacles collision, reducing time interval, decreasing the path traveling cost and satisfying the kinematics constraints. In this paper, the free Cartesian space map of 2-DOF arm is constructed to attain the joints variable at each point without collision. The D*algorithm and Euclidean distance are applied to obtain the exact and estimated distances to the goal respectively. The modified Particle Swarm Optimization al

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Publication Date
Thu Feb 01 2018
Journal Name
Journal Of Engineering
Optimization of Cutting Parameters on Delamination of Drilling Glass-Polyester Composites
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This paper attempted to study the effect of cutting parameters (spindle speed and feed rate) on delamination phenomena during the drilling glass-polyester composites. Drilling process was done by CNC machine with 10 mm diameter of high-speed steel (HSS) drill bit. Taguchi technique with L16 orthogonal layout was used to analyze the effective parameters on delamination factor. The optimal experiment was no. 13 with spindle speed 1273 rpm and feed 0.05 mm/rev with minimum delamination factor 1.28.                                       &

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Publication Date
Tue Dec 31 2013
Journal Name
Al-khwarizmi Engineering Journal
Design of an Adaptive PID Neural Controller for Continuous Stirred Tank Reactor based on Particle Swarm Optimization
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 A particle swarm optimization algorithm and neural network like self-tuning PID controller for CSTR system is presented. The scheme of the discrete-time PID control structure is based on neural network and tuned the parameters of the PID controller by using a particle swarm optimization PSO technique as a simple and fast training algorithm. The proposed method has advantage that it is not necessary to use a combined structure of identification and decision because it used PSO. Simulation results show the effectiveness of the proposed adaptive PID neural control algorithm in terms of minimum tracking error and smoothness control signal obtained for non-linear dynamical CSTR system.

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Publication Date
Thu Apr 01 2021
Journal Name
Computer Methods And Programs In Biomedicine
A hybrid approach based on multiple Eigenvalues selection (MES) for the automated grading of a brain tumor using MRI
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Publication Date
Tue Sep 08 2020
Journal Name
Baghdad Science Journal
Modified BFGS Update (H-Version) Based on the Determinant Property of Inverse of Hessian Matrix for Unconstrained Optimization
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The study presents the modification of the Broyden-Flecher-Goldfarb-Shanno (BFGS) update (H-Version) based on the determinant property of inverse of Hessian matrix (second derivative of the objective function), via updating of the vector s ( the difference between the next solution and the current solution), such that the determinant of the next inverse of Hessian matrix is equal to the determinant of the current inverse of Hessian matrix at every iteration. Moreover, the sequence of inverse of Hessian matrix generated by the method would never  approach a near-singular matrix, such that the program would never break before the minimum value of the objective function is obtained. Moreover, the new modification of BFGS update (H-vers

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Publication Date
Tue Jun 01 2021
Journal Name
Journal Of Petroleum Exploration And Production Technology
Incremental and acceleration production estimation and their effect on optimization of well infill locations in tight gas reservoirs
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Abstract<p>The main role of infill drilling is either adding incremental reserves to the already existing one by intersecting newly undrained (virgin) regions or accelerating the production from currently depleted areas. Accelerating reserves from increasing drainage in tight formations can be beneficial considering the time value of money and the cost of additional wells. However, the maximum benefit can be realized when infill wells produce mostly incremental recoveries (recoveries from virgin formations). Therefore, the prediction of incremental and accelerated recovery is crucial in field development planning as it helps in the optimization of infill wells with the assurance of long-term economic sustainabi</p> ... Show More
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Publication Date
Sun Feb 22 2026
Journal Name
Pakistan Journal Of Pharmaceutical Sciences
Optimization And Development Of Ondansetron HCl Nanocrystals By Using D-Optimal Design Expert® And In-Vitro Characterization
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Background: Over the last few years, nanocrystal technology has expanded to improve the bioavailability of poorly water-soluble drugs, which is challenging. Nanocrystals (NCs) exhibit many properties, such as enhancing drug solubility, dissolution, oral absorption, and high drug loading. Ondansetron hydrochloride (ONH) is an antiemetic drug that antagonizes a serotonin 5-HT3 receptor in the peripheral and central nervous system and is widely prescribed for the management of chemotherapy and radiotherapy-induced vomiting and nausea, as well as for postoperative nausea. ONH exhibits approximately 60% bioavailability due to its poor solubility and first-pass metabolism in the liver. Its solubility is pH-dependent, its precipitates abov

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