Showing 141 - 160 results of 474 for search '(((( data code algorithm ) OR ( data modeling algorithm ))) OR ( element method algorithm ))*', query time: 0.12s Refine Results
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    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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  3. 143

    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. …”
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    Data Endowment as a Digital Waqf: An Islamic Ethical Framework for AI Development by Abdulqadir J. Nashwan (11659453)

    Published 2025
    “…<p dir="ltr">In the era of artificial intelligence (AI), data is often called the new oil—an essential asset for training algorithms and fueling intelligent systems. …”
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    A flexible genetic algorithm-fuzzy regression approach for forecasting: The case of bitumen consumption by Azadeh, Ali

    Published 2019
    “…This study aims to introduce a flexible genetic algorithm-fuzzy regression approach for forecasting the future bitumen consumption. …”
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  9. 149

    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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  10. 150

    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. …”
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    SemIndex+: A semantic indexing scheme for structured, unstructured, and partly structured data by Tekli, Joe

    Published 2018
    “…This paper describes SemIndex+, a semantic-aware indexing and querying framework that allows semantic search, result selection, and result ranking of structured (relational DB-style), unstructured (IR-style), and partly structured (NoSQL) data. Various weighting functions and a parallelized search algorithm have been developed for that purpose and are presented here. …”
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    Stochastic management of hybrid AC/DC microgrids considering electric vehicles charging demands by Peng, Wang

    Published 2020
    “…In order to mitigate the charging effects of electric vehicles on the hybrid AC–DC microgrid operation, some remotely switches are considered in the system which make it possible for changing the topology and power flow way. In order to model the uncertainty effects, a data-driven framework based on point estimate method and support vector machine is developed. …”
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  16. 156

    A Data-Driven Decision-Making Framework for Fleet Management in the Government Sector of Dubai by ALGHANEM, HANI SUBHI MOHD

    Published 2024
    “…My research aims to develop a data-driven decision support framework for fleet management, focusing on leveraging advanced algorithms, including decision trees and random forests, to generate domain-specific AI models. …”
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  17. 157

    Blue collar laborers’ travel pattern recognition: Machine learning classifier approach by Aya Hasan Alkhereibi (17151070)

    Published 2021
    “…Raw data preprocessing and outliers detection and filtering algorithms were applied at the first stage of the analysis, and consequently, an activity-based travel matrix was developed for each household. …”
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    KNNOR: An oversampling technique for imbalanced datasets by Ashhadul Islam (16869981)

    Published 2021
    “…<p>Predictive performance of Machine Learning (ML) models rely on the quality of data used for training the models. …”
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