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Showing 161 - 180 results of 571 for search '(((( data modeling algorithm ) OR ( data processing algorithm ))) OR ( element study algorithm ))*', query time: 0.15s Refine Results
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    Performance of artificial intelligence models in estimating blood glucose level among diabetic patients using non-invasive wearable device data by Arfan Ahmed (17541309)

    Published 2023
    “…Our experimental design included Data Collection, Feature Engineering, ML model selection/development, and reporting evaluation of metrics.…”
  6. 166

    Automatic and Intelligent Stressor Identification Based on Photoplethysmography Analysis by Sami Elzeiny (16891521)

    Published 2021
    “…This work leverages the output of wearable technology to provide automatic stress and stressor identification model. In particular, this study proposes a novel algorithm that first detects instances of stress and then classifies the stressor type using photoplethysmography (PPG) data from wearable smartwatches. …”
  7. 167

    Random Forest Bagging and X‐Means Clustered Antipattern Detection from SQL Query Log for Accessing Secure Mobile Data by Rajesh Kumar Dhanaraj (19646269)

    Published 2021
    “…In addition, for grouping similar antipatterns, a clustering process was performed to eradicate the design errors. …”
  8. 168

    Severity-Based Prioritized Processing of Packets with Application in VANETs by Ala Al-Fuqaha (4434340)

    Published 2019
    “…In this study, we propose a generic prioritization and resource management algorithm that can be used to prioritize processing of received packets in vehicular networks. …”
  9. 169

    Diagnostic structure of visual robotic inundated systems with fuzzy clustering membership correlation by Hariprasath Manoharan (14157966)

    Published 2023
    “…Additionally, a clustering algorithm with a fuzzy membership function is implemented, allowing the robots to advance in accordance with predefined clusters and arrive at their starting place within a predetermined amount of time. …”
  10. 170

    Short-Term Load Forecasting in Active Distribution Networks Using Forgetting Factor Adaptive Extended Kalman Filter by Mena S. ElMenshawy (17983807)

    Published 2023
    “…A few research studies focused on developing data filtering algorithm for the load forecasting process using approaches such as Kalman filter, which has good tracking capability in the presence of noise in the data collection process. …”
  11. 171

    Predict Student Success and Performance factors by analyzing educational data using data mining techniques by ATIF, MUHAMMAD

    Published 2022
    “…The model is then applied to data collected from a reputable university that included 126,698 records with twenty-six (26) initial data attributes. …”
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  12. 172

    Defining quantitative rules for identifying influential researchers: Insights from mathematics domain by Ghulam Mustafa (458105)

    Published 2024
    “…Within each categorical grouping, we meticulously selected the five most pivotal parameters. This selection process was guided by an importance score, that was derived after assessing its influence on the model's performance in the classification of data pertaining to both awardees and non awardees. …”
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    Privacy-Preserving Fog Aggregation of Smart Grid Data Using Dynamic Differentially-Private Data Perturbation by Fawaz Kserawi (16904859)

    Published 2022
    “…We describe our differentially-private model with flexible constraints and a dynamic window algorithm to maintain the privacy-budget loss in infinitely generated time-series data. …”
  17. 177

    Bee Colony Algorithm for Proctors Assignment. by Mansour, Nashat

    Published 2015
    “…The Bee Colony algorithm is a recent population-based search algorithm that mimics the natural behavior of swarms of honey bees during the process of collecting food. …”
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  18. 178

    Oversampling techniques for imbalanced data in regression by Samir Brahim Belhaouari (9427347)

    Published 2024
    “…For tabular data we conducted a comprehensive experiment using various models trained on both augmented and non-augmented datasets, followed by performance comparisons on test data. …”
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