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Showing 121 - 140 results of 458 for search '(((( data models algorithm ) OR ( data lacking algorithm ))) OR ( element method algorithm ))', query time: 0.14s Refine Results
  1. 121

    Block constrained pressure residual preconditioning for two-phase flow in porous media by mixed hybrid finite elements by Stefano Nardean (14151900)

    Published 2023
    “…<p dir="ltr">This work proposes an original preconditioner that couples the Constrained Pressure Residual (CPR) method with block preconditioning for the efficient solution of the linearized systems of equations arising from fully implicit multiphase flow models. …”
  2. 122

    Integration of Artificial Intelligence in E-Procurement of the Hospitality Industry: A Case Study in the UAE by Mathew, Elezabeth

    Published 2020
    “…The data analytics maturity model is used as the conceptual model for evaluating both data analytics and data governance in this research. …”
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  3. 123

    Eye-Clustering: An Enhanced Centroids Prediction for K-means Algorithm by Nasser, Youssef

    Published 2024
    “…To achieve this goal, supervised machine learning was employed to train models on graphs with labeled data points, where each graph contains a set of points and a label indicating the centroid determined by K-means. …”
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    masterThesis
  4. 124

    A method for data path synthesis using neural networks by Harmanani, H.

    Published 2017
    “…Presents a deterministic parallel algorithm to solve the data path allocation problem in high-level synthesis. …”
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    conferenceObject
  5. 125

    Indexing Arabic texts using association rule data mining by Haraty, Ramzi A.

    Published 2019
    “…Purpose The purpose of this paper is to propose a new model to enhance auto-indexing Arabic texts. The model denotes extracting new relevant words by relating those chosen by previous classical methods to new words using data mining rules. …”
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    article
  6. 126

    Data mining approach to predict student's selection of program majors by SIDDARTHA, SHARMILA

    Published 2019
    “…The approach includes a methodology to manage data mining projects, sampling techniques to handle imbalanced data and multiclass data, a set of classification algorithms to predict and measures to evaluate performance of models. …”
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  7. 127

    Use of Data Mining Techniques to Detect Fraud in Procurement Sector by AL HAMMADI, SUMAYYA ABDULLA

    Published 2022
    “…The method used in this research is a classification of models and algorithms used in data mining. All techniques also will be studied; they include clustering, tracking patterns, classifications and outlier detection. …”
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  8. 128

    An efficient approach for textual data classification using deep learning by Abdullah Alqahtani (7128143)

    Published 2022
    “…<p dir="ltr">Text categorization is an effective activity that can be accomplished using a variety of classification algorithms. In machine learning, the classifier is built by learning the features of categories from a set of preset training data. …”
  9. 129
  10. 130

    A method for optimizing test bus assignment and sizing for system-on-a-chip by Harmanani, Haidar M.

    Published 2017
    “…Test access mechanism (TAM) is an important element of test access architectures for embedded cores and is responsible for on-chip test patterns transport from the source to the core under test to the sink. …”
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    conferenceObject
  11. 131

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

    Published 2022
    “…The LR model showed the foremost predictions of ground loss as compared to all the other models analyzed. …”
  12. 132

    Assessment of static pile design methods and non-linear analysis of pile driving by Abou-Jaoude, Grace G.

    Published 2006
    “…The pile/soil interaction system is described by a mass/spring/dashpot system where the properties of each component are derived from rigorous analytical solutions or finite element analysis. The outcome of this research is an algorithm that can be used to predict pile displacement and driving stresses. …”
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    masterThesis
  13. 133

    Evolutionary algorithms for state justification in sequential automatic test pattern generation by El-Maleh, Aiman H.

    Published 2005
    “…A common search operation in sequential Automatic Test Pattern Generation is to justify a desired state assignment on the sequential elements. State justification using deterministic algorithms is a difficult problem and is prone to many backtracks, which can lead to high execution times. …”
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    article
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  16. 136

    Online Recruitment Fraud (ORF) Detection Using Deep Learning Approaches by Natasha Akram (20749538)

    Published 2024
    “…Exploratory Data Analysis (EDA) highlights the class imbalance problem in detecting fake jobs, which tends the model to act aggressively toward the minority class. …”
  17. 137

    Customs Trade Facilitation and Compliance for Ecommerce using Blockchain and Data Mining by Alqaryouti, Omar

    Published 2021
    “…Additionally, the Cross Industry Standard Process for Data Mining (CRISP-DM) methodology is employed for modelling the two proposed clustering algorithms to identify transactional risks. …”
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  18. 138

    An App for Navigating Patient Transportation and Acute Stroke Care in Northwestern Ontario Using Machine Learning: Retrospective Study by Ayman Hassan (14426412)

    Published 2024
    “…The data were distributed for training (35%), testing (35%), and validation (30%) of the prediction model.…”
  19. 139

    NOVEL STACKING CLASSIFICATION AND PREDICTION ALGORITHM BASED AMBIENT ASSISTED LIVING FOR ELDERLY by JINESH, PADIKKAPPARAMBIL

    Published 2022
    “…Various sensors and equipment are installed in the AAL context to collect a wide variety of data. Furthermore, AAL could be the motivating technique for the most recent care models by working as an adjunct. …”
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  20. 140

    Artificial intelligence-based methods for fusion of electronic health records and imaging data by Farida Mohsen (16994682)

    Published 2022
    “…In our analysis, a typical workflow was observed: feeding raw data, fusing different data modalities by applying conventional machine learning (ML) or deep learning (DL) algorithms, and finally, evaluating the multimodal fusion through clinical outcome predictions. …”