Showing 61 - 80 results of 393 for search '(((( develop based algorithms ) OR ( element updated algorithm ))) OR ( data fitting algorithm ))', query time: 0.11s Refine Results
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    Novel Peak Detection Algorithms for Pileup Minimization in Gamma Ray Spectroscopy by Raad, M.W.

    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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    article
  4. 64

    A Modular Reconfigurable Architecture for Asymmetric and Symmetric-key Cryptographic Algorithms by Zaidi, Ali Mustafa

    Published 2007
    “…Numerous such algorithms have been devised, and many have found popularity in different domains. …”
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    masterThesis
  5. 65

    A Multiswarm Intelligence Algorithm for Expensive Bound Constrained Optimization Problems by Wali Khan Mashwani (14590504)

    Published 2021
    “…In this paper, a multiswarm-intelligence-based algorithm (MSIA) is developed to cope with bound constrained functions. …”
  6. 66

    A Genetic Algorithm for Improving Accuracy of Software Quality Predictive Models by Azar, Danielle

    Published 2010
    “…In this work, we present a genetic algorithm to optimize predictive models used to estimate software quality characteristics. …”
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    article
  7. 67

    A new family of multi-step quasi-Newton algorithms for unconstrained optimization by Obeid, Samir

    Published 1999
    “…It concentrates on deriving a variable-metric family of minimum curvature algorithms for unconstrained optimization. The derivation is based on considering a rational model, with a certain tuning parameter, where the aim is to develop a general framework that encompasses all possible two-step minimum curvature algorithms generated by appropriate parameter choices. …”
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    article
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    UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data by Behrouz Ahadzadeh (19757022)

    Published 2024
    “…To overcome these challenges, a new FS algorithm named Uniform-solution-driven Binary Feature Selection (UniBFS) has been developed in this study. …”
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    BioNetApp: An interactive visual data analysis platform for molecular expressions by Ali M. Roumani (18615124)

    Published 2019
    “…BioNetApp also provides data clustering based on molecular concentrations using Self Organizing Maps (SOM), K-Means, K-Medoids, and Farthest First algorithms.…”
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    Development of multivariable PID controller gains in presence of measurement noise by Saab, Samer S.

    Published 2017
    “…The development of the proposed optimal algorithm is based on minimising a stochastic performance index in presence of erroneous initial conditions, white measurement noise, and white process noise. …”
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    article
  15. 75

    Environmental/economic power dispatch using multiobjective evolutionary algorithms: a comparative study by Abido, M.A.

    Published 2003
    “…A comparative study of newly developed Pareto-based multiobjective evolutionary algorithms (MOEA) applied to a nonlinear power system multiobjective optimization problem is presented in this paper. …”
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    article
  16. 76

    Developing an online hate classifier for multiple social media platforms by Joni Salminen (7434770)

    Published 2020
    “…While all the models significantly outperform the keyword-based baseline classifier, XGBoost using all features performs the best (F1 = 0.92). …”
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    Topology design of switched enterprise networks using a fuzzy simulated evolution algorithm by Youssef, H.

    Published 2020
    “…In this paper, we present an approach based on Simulated Evolution algorithm for the design of SEN topology. …”
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    article
  18. 78

    Topology design of switched enterprise networks using a fuzzy simulated evolution algorithm by Youssef, H.

    Published 2020
    “…In this paper, we present an approach based on Simulated Evolution algorithm for the design of SEN topology. …”
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    article
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    Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks by Najam Us Sahar Riyaz (22927843)

    Published 2025
    “…This work identifies the most reliable machine learning (ML) strategies for forecasting corrosion inhibitor efficiency before synthesis, thereby shortening development cycles and reducing experimental cost. Drawing on more than fifteen harmonized datasets that span pyrimidines, ionic liquids, graphene oxides, and additional compound families, we benchmark traditional algorithms, such as artificial neural networks, support vector machines, k-nearest neighbors, random forests, against advanced graph-based and deep architectures including three-level directed message-passing neural networks, 2D3DMol-CIC, and graph convolutional networks. …”