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Bee Colony Algorithm for Proctors Assignment.
Published 2015“…The search accomplished by three types of bees over a number of iterations aiming to find the source with the highest nectar value (fitness value of a candidate solution). We apply the Bee Colony algorithm to previously published data. Experimental results show good solutions that maximize the preferences of proctors while preserving the fairness of the workload given to proctors. …”
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Bee colony algorithm for assigning proctors to exams. (c2013)
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An ant colony optimization algorithm to improve software quality prediction models
Published 2011“…We use an ant colony optimization algorithm in the adaptation process. …”
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Metaheuristic Optimization Algorithms for Training Artificial Neural Networks
Published 2012“…A few metaheuristic optimization techniques have been applied to increase the effectiveness of the training process. The Cuckoo Search (CS) algorithm is a recently developed meta-heuristic optimization algorithm which is suitable for solving optimization problems. …”
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Estimation of the methanol loss in the gas hydrate prevention unit using the artificial neural networks: Investigating the effect of training algorithm on the model accuracy
Published 2023“…Adjusting the weight and bias of the ANN model using an optimization algorithm is known as the training process. …”
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Classifying Maqams of Qur'anic Recitations Using Deep Learning
Published 2021“…An accuracy of 95.7% on the test set is obtained using a 5-layer deep ANN which was trained using 26 input features. …”
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A parallel ant colony optimization to globally optimize area in high-level synthesis. (c2011)
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Extended Behavioral Modeling of FET and Lattice-Mismatched HEMT Devices
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A Survey of Audio Enhancement Algorithms for Music, Speech, Bioacoustics, Biomedical, Industrial, and Environmental Sounds by Image U-Net
Published 2023“…We will discuss the need for AE, U-Net comparison to other DNNs, the benefits of converting the audio to 2D, input representations that are useful for different AE applications, the architecture of vanilla U-Net and the pre-trained models, variations in vanilla architecture incorporated in different E models, and the state-of-the-art AE algorithms based on U-Net in various applications. …”
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Using genetic algorithms to optimize software quality estimation models
Published 2004“…In the first approach, we assume the existence of several models, and we use a genetic algorithm to combine them, and adapt them to a given data set. …”
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A reduced model for phase-change problems with radiation using simplified PN approximations
Published 2025“…The integro-differential equation for the full radiative transfer is replaced by a set of differential equations which are independent of the angle variable and easy to solve using conventional computational methods. To solve the coupled equations, we implement a second-order implicit scheme for the time integration and a mixed finite element method for the space discretization. …”
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Estimating Construction Project Duration Using a Machine Learning Algorithm
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Brain Source Localization in the Presence of Leadfield Perturbations
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Day-Ahead Load Demand Forecasting in Urban Community Cluster Microgrids Using Machine Learning Methods
Published 2022“…In addition, three distinct optimization techniques are used to find the optimum ANN training algorithm: Levenberg–Marquardt, Bayesian Regularization, and Scaled Conjugate Gradient. …”