Showing 141 - 160 results of 594 for search '(( element mean algorithm ) OR ((( data code algorithm ) OR ( based modeling algorithm ))))', query time: 0.14s Refine Results
  1. 141

    Wild Blueberry Harvesting Losses Predicted with Selective Machine Learning Algorithms by Humna Khan (17541972)

    Published 2022
    “…Statistical parameters i.e., mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R<sup>2</sup>), were used to assess the prediction accuracy of the models. The results of the correlation matrices showed that the blueberry yield and losses (leaf loss, blower loss) had medium to strong correlations accessed based on the correlation coefficient (r) range 0.37–0.79. …”
  2. 142

    On the protection of power system: Transmission line fault analysis based on an optimal machine learning approach by Md. Sihab Uddin (17542488)

    Published 2022
    “…The design is carried out based on the selection of the optimal model parameters using a search optimization algorithm called GridSearchCV. …”
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    Spectral energy balancing system with massive MIMO based hybrid beam forming for wireless 6G communication using dual deep learning model by Ramesh Sundar (19326046)

    Published 2024
    “…The computational cost and performance estimations are improved, and the metrics are clearly visualized on this paper based on improved beamforming procedures as well as the proposed approach of DDN based Multi-Resolution Code Book performance metrics are estimated clearly with proper mathematical model investigations. …”
  5. 145

    Correlation Clustering via s-Club Cluster Edge Deletion by Makarem, Norma

    Published 2023
    “…In certain situations, the requirement for clusters to be cliques was deemed excessively stringent, leading to the proposal of alternative relaxed clique models for dense subgraphs, such as s-club. In this work, we implement three approaches to tackle the 2-club clustering via edge deletion: a heuristic approach based on the influence of the edge to resolve maximum conflicts, a parameterized algorithm in which by deleting a maximum of k edges, the graph can be transformed into a 2-club cluster based on a branching algorithm, and the approach in Integer Linear Programming to find the optimized solution in an integer formulation. …”
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    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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    A Novel Fault Diagnosis of Uncertain Systems Based on Interval Gaussian Process Regression: Application to Wind Energy Conversion Systems by Majdi Mansouri (16869885)

    Published 2020
    “…In the proposed IGPR-RF technique, the effective interval-valued nonlinear statistical features are extracted and selected using the IGPR model and then fed to the RF algorithm for fault classification purposes. …”
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    Joint energy-distortion aware algorithms for cooperative video streaming over LTE networks by Yaacoub, Elias

    Published 2013
    “…Videos with single description coding (SDC), multiple description coding (MDC), and scalable video coding (SVC) are considered. …”
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    article
  17. 157

    Optimization of Interval Type-2 Fuzzy Logic System Using Grasshopper Optimization Algorithm by Saima Hassan (14918003)

    Published 2022
    “…The forecasting performance of the proposed model is compared with other population-based optimized IT2-FLS including genetic algorithm and artificial bee colony optimization algorithm. …”
  18. 158

    Stochastic management of hybrid AC/DC microgrids considering electric vehicles charging demands by Peng, Wang

    Published 2020
    “…A novel evolving solution based on flower pollination algorithm is also proposed to solve the problem optimally. …”
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    article
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    The automation of the development of classification models and improvement of model quality using feature engineering techniques by Sjoerd Boeschoten (17347045)

    Published 2023
    “…<p>Recently pipelines of machine learning-based classification models have become important to codify, orchestrate, and automate the workflow to produce an effective machine learning model. …”