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Selection of the learning gain matrix of an iterative learning control algorithm in presence of measurement noise
Published 2005“…The main purpose of this paper is to supply to the iterative learning control (ILC) designer guidelines to select the corresponding learning gain in order to achieve this control objective. …”
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Haplotype inference by pure-parsimony using revamped delayed haplotype selection. (c2011)
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masterThesis -
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Exploiting Sparsity in Amplify-and-Forward Broadband Multiple Relay Selection
Published 2019“…Therefore, to solve this problem and enhance the spatial and frequency diversity orders of large amplify and forward cooperative communication networks, in this paper, we develop three multiple relay selection and distributed beamforming techniques that exploit sparse signal recovery theory to process the subcarriers using the low complexity orthogonal matching pursuit algorithm (OMP). …”
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Arabic Text Classification Using Modified Artificial Bee Colony Algorithm for Sentiment Analysis: The Case of Jordanian Dialect
Published 2022“…The second phase, modified the Artificial Bee Colony (ABC) Algorithm, with Upper Confidence Bound (UCB) Algorithm, to promote the exploitation ability for the minimum dimension, to get the minimum number of the optimal feature, then using forward feature selection strategy by four classifiers of machine learning algorithms: (K-Nearest Neighbors (KNN), Support vector machines (SVM), Naïve-Bayes (NB), and Polynomial Neural Networks (PNN). …”
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Intelligent Bilateral Client Selection in Federated Learning Using Game Theory
Published 2022“…Our solution involves designing (1) preference functions for the client IoT devices and federated servers to allow them to rank each other according to several factors such as accuracy and price, (2) intelligent matching algorithms that take into account the preferences of both parties in their design, and (3) bootstrapping technique that capitalizes on the collaboration of multiple federated servers in order to assign initial accuracy value for the new connected IoT devices. …”
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masterThesis -
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Parallel Algorithms for Distinguishing Nondeterministic Finite State Machines
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doctoralThesis -
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Experimental Investigation and Comparative Evaluation of Standard Level Shifted Multi-Carrier Modulation Schemes With a Constraint GA Based SHE Techniques for a Seven-Level PUC Inv...
Published 2019“…Different standard multicarrier sinusoidal pulse-width modulation techniques (SPWMs) are adapted for the generation of switching gate signals for the PUC power switches, and these SPWMs are compared with novel optimization-based selective harmonic elimination (SHE) that employs genetic algorithm (GA) for solving nonlinear SHE equation with a constraint that eliminated all third-order harmonics efficiently. …”
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Gene selection for microarray data classification based on Gray Wolf Optimizer enhanced with TRIZ-inspired operators
Published 2021“…In order to avoid these pitfalls, gene selection is needed. …”
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Genetic and heuristic algorithms for regrouping service sites. (c2000)
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masterThesis -
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An Improved Genghis Khan Optimizer based on Enhanced Solution Quality Strategy for Global Optimization and Feature Selection Problems
Published 2024“…Feature selection (FS) is the activity of defining the most contributing feature subset among all used features to improve the superiority of datasets with a large number of dimensions by selecting significant features and eliminating redundant and irrelevant ones. …”
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A multi-class discriminative motif finding algorithm for autosomal genomic data. (c2015)
Published 2016“…Our algorithm first performs a feature selection step to define differentiable SNPs. …”
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masterThesis -
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New Hardware Algorithms and Designs for Montgomery Modular Inverse Computation in Galois Fields GF(p) and GF(2n)
Published 2002“…We suggest a new correction phase for a previously proposed almost Montgomery inverse algorithm to calculate the inversion in hardware. It is also presented how to obtain a fast hardware algorithm to compute the inverse by multi-bit shifting method. …”
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masterThesis -
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Predicting Plasma Vitamin C Using Machine Learning
Published 2022“…Variables were selected based on a known or hypothesized relationship with plasma vitamin C, and variables that are expensive or difficult to obtain were excluded in order to more closely replicate the situation of a real health application. …”
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Enhanced PSO-Based NN for Failures Detection in Uncertain Wind Energy Systems
Published 2023“…Therefore, an enhanced particle swarm optimization (PSO), data reduction, and interval-valued representation are proposed. First, a feature selection tool using PSO Algorithm is developed. Then, in order to maximize the diversity between data samples and improve the effectiveness of using PSO algorithm for feature selection, the Euclidean distance metric is used in order to reduce the data and maximize the diversity between data samples. …”
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Interval-Valued SVM Based ABO for Fault Detection and Diagnosis of Wind Energy Conversion Systems
Published 2022“…Then, to improve even more the performances of the developed interval-valued SVM, multiscale data representation will be used to develop multiscale extensions of interval-valued SVM. Next, as a feature selection tool, an improved extension of Artificial Butterfly Optimization (ABO) algorithm is used in order to extract the significant features from data and improve the diagnosis results of multiscale interval SVM. …”
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