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Optimal selection of the forgetting matrix into an iterative learning control algorithm
Published 2005“…A recursive optimal algorithm, based on minimizing the input error covariance matrix, is derived to generate the optimal forgetting matrix and the learning gain matrix of a P-type iterative learning control (ILC) for linear discrete-time varying systems with arbitrary relative degree. …”
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TIDCS: A Dynamic Intrusion Detection and Classification System Based Feature Selection
Published 2020“…TIDCS reduces the number of features in the input data based on a new algorithm for feature selection. Initially, the features are grouped randomly to increase the probability of making them participating in the generation of different groups, and sorted based on their accuracy scores. …”
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A Survey of Data Clustering Techniques
Published 2023“…This survey examines seven widely recognized clustering techniques, namely k-means, G-means, DBSCAN, Agglomerative hierarchical clustering, Two-stage density (DBSCAN and k-means) algorithm, Two-levels (DBSCAN and hierarchical) clustering algorithm, and Two-stage MeanShift and K-means clustering algorithm and compares them over a real dataset - The Blockchain dataset, including prominent cryptocurrencies like Binance, Bitcoin, Doge, and Ethereum, under several metrics such as silhouette coefficient, Calinski-Harabasz, Davies-Bouldin Index, time complexity, and entropy.…”
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Genetic and heuristic algorithms for regrouping service sites. (c2000)
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masterThesis -
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Deep learning-based user experience evaluation in distance learning
Published 2023“…More than 160,000 tweets, addressing conditions related to the major change in the education system, were gathered from Twitter social network and deep learning-based sentiment analysis models and topic models based on latent dirichlet allocation (LDA) algorithm were developed and analyzed. …”
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A genetic algorithm for corrective retesting. (c1995)
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A stochastic iterative learning control algorithm with application to an induction motor
Published 2004“…A recursive optimal algorithm, based on minimizing the input error covariance matrix, is derived to generate the learning gain matrix of a P-type ILC for linear discrete-time varying systems with arbitrary relative degree. …”
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Stochastic P-type/D-type iterative learning control algorithms
Published 2003“…This paper presents stochastic algorithms that compute optimal and sub-optimal learning gains for a P-type iterative learning control algorithm (ILC) for a class of discrete-time-varying linear systems. …”
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On Higher-Order Iterative Learning Control Algorithm in Presence of Measurement Noise
Published 2005“…Higher-Order Iterative Learning Control (HO-ILC) algorithms use past system control information from more than one past iterative cycle. …”
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Clustering/partitioning algorithms and comparative analysis
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masterThesis -
54
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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A multi-class discriminative motif finding algorithm for autosomal genomic data. (c2015)
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masterThesis -
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Deep Learning-Based Fault Diagnosis of Photovoltaic Systems: A Comprehensive Review and Enhancement Prospects
Published 2021“…Recently, due to the enhancement of computing capabilities, the increase of the big data use, and the development of effective algorithms, the deep learning (DL) tool has witnessed a great success in data science. …”
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