Showing 61 - 80 results of 443 for search '(((( data modeling algorithm ) OR ( involves learning algorithms ))) OR ( element data algorithm ))', query time: 0.13s Refine Results
  1. 61

    Sentiment Analysis of Dialectal Speech: Unveiling Emotions through Deep Learning Models by EZZELDIN, KHALED MOHAMED KHALED

    Published 2024
    “…Dialect Speech Sentiment Analysis is an evolutional field where machine learning algorithms are utilized to detect emotions in spoken language. …”
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    Correlation Clustering via s-Club Cluster Edge Deletion by Makarem, Norma

    Published 2023
    Subjects: “…Cluster analysis -- Data processing…”
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    masterThesis
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    Energy utilization assessment of a semi-closed greenhouse using data-driven model predictive control by Farhat Mahmood (15468854)

    Published 2021
    “…The proposed model predictive control framework is flexible and can be applied to other greenhouse systems by tuning the model on the new data set.…”
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    Integration of Artificial Intelligence in E-Procurement of the Hospitality Industry: A Case Study in the UAE by Mathew, Elezabeth

    Published 2020
    “…Various descriptive, diagnostic, predictive, and prescriptive analysis is done on the e-procurement data. The deep learning model developed can perform thousands of routine and, repetitive tasks within a fairly short period compared to what it would take for a human being without any compromise on the quality of work. …”
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  9. 69

    Calibration of building model based on indoor temperature for overheating assessment using genetic algorithm: Methodology, evaluation criteria, and case study by Mutasim Baba, Fuad

    Published 2022
    “…This methodology includes a variance-based sensitivity analysis to determine building parameters that significantly influence indoor air temperatures, the Multi-Objective Genetic Algorithm to calibrate different rooms simultaneously based on the significant param eters identified by the sensitivity analysis, and new evaluation criteria to achieve a high-accuracy calibrated model. …”
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  10. 70

    Sentiment Analysis of the Emirati Dialect text using Ensemble Stacking Deep Learning Models by AL SHAMSI, ARWA AHMED

    Published 2023
    “…For the basic machine learning algorithms, LR, NB, SVM, RF, DT, MLP, AdaBoost, GBoost, and an ensemble model of machine learning classifiers were used. …”
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    Evaluation of Aerosol Optical Depth and Aerosol Models from VIIRS Retrieval Algorithms over North China Plain by Jun Zhu (84054)

    Published 2017
    “…The VIIRS Environmental Data Record data (VIIRS_EDR) is produced operationally by NOAA, and is based on the MODIS atmospheric correction algorithm. …”
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    A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method by Amit Kumar Balyan (18288964)

    Published 2022
    “…Due to a limited training dataset, an ML-based IDS generates a higher false detection ratio and encounters data imbalance issues. 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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    Prediction of EV Charging Behavior Using Machine Learning by Shahriar, Sakib

    Published 2021
    “…Using data-driven tools and machine learning algorithms to learn the EV charging behavior can improve scheduling algorithms. …”
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    article
  17. 77

    Intelligent Bilateral Client Selection in Federated Learning Using Game Theory by Wehbi, Osama

    Published 2022
    “…Federated Learning (FL) is a novel distributed privacy-preserving learning paradigm, which enables the collaboration among several participants (e.g., Internet of Things devices) for the training of machine learning models. …”
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    masterThesis
  18. 78

    Label dependency modeling in Multi-Label Naïve Bayes through input space expansion by PKA Chitra (21749216)

    Published 2024
    “…To accommodate the heterogeneity of the expanded input space, we refine the likelihood parameters of iMLNB using a joint density function, which is adept at handling the amalgamation of data types. We subject our enhanced iMLNB model to a rigorous empirical evaluation, utilizing six benchmark datasets. …”
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    Information reconciliation through agent controlled graph model. (c2018) by Saba, Rita

    Published 2018
    “…Multiple models have been proposed and different techniques and data structures were used. …”
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    masterThesis