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testing algorithm » cosine algorithm (Expand Search)
method algorithm » mould algorithm (Expand Search)
using algorithm » cosine algorithm (Expand Search)
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UML-based regression testing for OO software
Published 2010“…When working with large and complex object-oriented systems, source code-based regression testing is usually costly. This paper proposes a programming-language-independent technique for regression test selection for object-oriented software based on Unified Modeling Language (UML 2.0) design diagrams. …”
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A hybrid distributed test generation method using deterministic and genetic algorithms
Published 2017“…The deterministic phase is based on the D-algorithm and generates an initial set of test vectors that are evolved in the genetic phase in order to achieve high fault coverage in a short time. …”
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conferenceObject -
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A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method
Published 2022“…To deal with the data-imbalance issue, this research develops an efficient hybrid network-based IDS model (HNIDS), which is utilized using the enhanced genetic algorithm and particle swarm optimization(EGA-PSO) and improved random forest (IRF) methods. …”
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Novel Peak Detection Algorithms for Pileup Minimization in Gamma Ray Spectroscopy
Published 2006“…A number of parameter estimation and digital online peak localisation algorithms are being developed, including a pulse classification technique which uses a simple peak search routine based on the smoothed first derivative method, which gave a percentage error of peak amplitude of less than 1%. …”
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A comparison of data mapping algorithms for parallel iterative PDE solvers
Published 1995“…We review and evaluate the performances of six data mapping algorithms used for parallel single-phase iterative PDE solvers with irregular 2-dimensional meshes on multicomputers. …”
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An enhanced k-means clustering algorithm for pattern discovery in healthcare data
Published 2015“…This paper studies data mining applications in healthcare. Mainly, we study k-means clustering algorithms on large datasets and present an enhancement to k-means clustering, which requires k or a lesser number of passes to a dataset. …”
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Efficient Dynamic Cost Scheduling Algorithm for Financial Data Supply Chain
Published 2021“…The primary tool used in the data supply chain is data batch processing which requires efficient scheduling. …”
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71
DG-Means – A Superior Greedy Algorithm for Clustering Distributed Data
Published 2022“…In this work, we present DG-means, which is a greedy algorithm that performs on distributed sets of data. …”
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masterThesis -
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Extended Behavioral Modeling of FET and Lattice-Mismatched HEMT Devices
Published 2016Subjects: Get full text
doctoralThesis -
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Power-constrained system-on-a-chip test scheduling using a genetic algorithm
Published 2006“…This paper presents an efficient approach for the test scheduling problem of core-based systems based on a genetic algorithm. …”
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Deep Learning-Based Short-Term Load Forecasting Approach in Smart Grid With Clustering and Consumption Pattern Recognition
Published 2021“…A k-Medoid based algorithm is employed for clustering whereas the forecasting models are generated for different clusters of load profiles. …”
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Parallel Algorithms for Distinguishing Nondeterministic Finite State Machines
Published 2015Get full text
doctoralThesis -
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