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Showing 1 - 20 results of 831 for search '(((( a making algorithm ) OR ( data using algorithm ))) OR ( elements method algorithm ))', query time: 0.13s Refine Results
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    An enhanced k-means clustering algorithm for pattern discovery in healthcare data by Haraty, Ramzi A.

    Published 2015
    “…This paper studies data mining applications in healthcare. Mainly, we study k-means clustering algorithms on large datasets and present an enhancement to k-means clustering, which requires k or a lesser number of passes to a dataset. …”
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    article
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    Properties of simulated annealing and genetic algorithms for mapping data to multicomputers by Mansour, Nashat

    Published 1997
    “…Some user parameters are included in the objective function and are architecture- or problem-dependent parameters. The others are used in the GA and SA algorithms. The fault tolerance capability is demonstrated by mapping data to a multicomputer with some faulty processors. …”
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    article
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    A Multiswarm Intelligence Algorithm for Expensive Bound Constrained Optimization Problems by Wali Khan Mashwani (14590504)

    Published 2021
    “…In this paper, a multiswarm-intelligence-based algorithm (MSIA) is developed to cope with bound constrained functions. …”
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    Exploring the Impact of Explainable Artificial Intelligence on Decision-making in Healthcare by MOHAMMAD, AHMAD HASAN

    Published 2023
    “…As artificial intelligence (AI) advances in healthcare, there is an increasing need to understand how AI-driven decision-making affects healthcare workers and patients. The development of explainable artificial intelligence (XAI) systems, which attempt to give visible and interpretable explanations for AI algorithms' judgements, is a vital part of AI in healthcare. …”
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    A multi-class discriminative motif finding algorithm for autosomal genomic data. (c2015) by Wehbe, Gioia Wahib

    Published 2016
    “…New technologies, such as Next-Generation Genome Sequencing, can now provide huge amounts of data in little time. Big initiatives such as the International Hapmap Project and the 1000 Genome project are making use of these technologies to provide the scientific community with a detailed genetic reference from different populations. …”
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    masterThesis
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    A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT by Dhananjay Bisen (19482454)

    Published 2023
    “…This research proposed a hybrid model for energy-efficient cluster formation and a head selection (E-CFSA) algorithm based on convolutional neural networks (CNNs) and a modified k-mean clustering (MKM) method for MEC. …”
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    Cryptocurrency Exchange Market Prediction and Analysis Using Data Mining and Artificial Intelligence by Al Rayhi, Nasser

    Published 2020
    “…One of the best algorithms in terms of the result is the Long Short Term Memory (LSTM) since it is based on recurrent neural networks which uses loop as a method to learn from heuristics data. …”
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    Forecasting the nearly unforecastable: why aren’t airline bookings adhering to the prediction algorithm? by Saravanan Thirumuruganathan (11038038)

    Published 2021
    “…The resulting model achieves an 89% predictive accuracy using historical data. A unique aspect of the model is the incorporation of self-competence, where the model defers when it cannot reasonably make a recommendation. …”
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    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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    Comparative analysis of metaheuristic load balancing algorithms for efficient load balancing in cloud computing by Jincheng Zhou (1887307)

    Published 2023
    “…This paper provides a comparative analysis of various metaheuristic load balancing algorithms for cloud computing based on performance factors i.e., Makespan time, degree of imbalance, response time, data center processing time, flow time, and resource utilization. …”