Showing 1 - 20 results of 565 for search '(( data modeling algorithm ) OR ((( presented data algorithm ) OR ( relevant data algorithm ))))', query time: 0.13s Refine Results
  1. 1

    UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data by Behrouz Ahadzadeh (19757022)

    Published 2024
    “…<p>Feature selection (FS) is a crucial technique in machine learning and data mining, serving a variety of purposes such as simplifying model construction, facilitating knowledge discovery, improving computational efficiency, and reducing memory consumption. …”
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    A neural networks algorithm for data path synthesis by Harmanani, Haidar M.

    Published 2003
    “…This paper presents a deterministic parallel algorithm to solve the data path allocation problem in high-level synthesis. …”
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  4. 4

    Allocating data to distributed-memory multiprocessors by genetic algorithms by Mansour, Nashat

    Published 2016
    “…We present three genetic algorithms (GAs) for allocating irregular data sets to multiprocessors. …”
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    Variable Selection in Data Analysis: A Synthetic Data Toolkit by Mitra, Rohan

    Published 2024
    “…Variable (feature) selection plays an important role in data analysis and mathematical modeling. This paper aims to address the significant lack of formal evaluation benchmarks for feature selection algorithms (FSAs). …”
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    Parallel physical optimization algorithms for allocating data to multicomputer nodes by Mansour, Nashat

    Published 1994
    “…Three parallel physical optimization algorithms for allocating irregular data to multicomputer nodes are presented. …”
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    Physical optimization algorithms for mapping data to distributed-memory multiprocessors by Mansour, Nashat

    Published 1992
    “…We present three parallel physical optimization algorithms for mapping data to distributed-memory multiprocessors, concentrating on irregular loosely synchronous problems. …”
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    masterThesis
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    DG-Means – A Superior Greedy Algorithm for Clustering Distributed Data by Assaf, Ali

    Published 2022
    “…In this work, we present DG-means, which is a greedy algorithm that performs on distributed sets of data. …”
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    masterThesis
  10. 10

    Improved Transportation Model with Internet of Things Using Artificial Intelligence Algorithm by Ayman Khallel Al-Ani (17541447)

    Published 2023
    “…Furthermore, a route management technique is combined with Artificial Intelligence (AI) algorithm to transmit the data to appropriate central servers. …”
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    Using Machine Learning Algorithms to Forecast Solar Energy Power Output by Ali Jassim Lari (22597940)

    Published 2025
    “…The data forecasting horizon used was a 24-h window in steps of 30 min. …”
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    Auto-indexing Arabic texts based on association rule data mining. (c2015) by Rouba G. Nasrallah

    Published 2015
    “…In this work, we propose a new model to enhance auto-indexing Arabic texts. Our model denotes extracting new relevant words by relating those chosen by the previous classical methods, to new words using data mining rules. …”
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    masterThesis
  14. 14

    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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    Predicting Dropouts among a Homogeneous Population using a Data Mining Approach by BILQUISE, GHAZALA

    Published 2019
    “…Our research relies solely on pre-college and college performance data available in the institutional database. Our research reveals that the Gradient Boosted Trees is a robust algorithm that predicts dropouts with an accuracy of 79.31% and AUC of 88.4% using only pre-enrollment data. …”
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    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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    Second-order conic programming for data envelopment analysis models by Mourad, Nahia

    Published 2022
    “…This paper constructs a second-order conic optimization problem unifying several DEA models. Moreover, it presents an algorithm that solves the former problem, and provides a MATLAB function associated with it. …”
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    An ant colony optimization algorithm to improve software quality prediction models by Azar, D.

    Published 2011
    “…Method This paper presents an adaptive approach that takes already built predictive models and adapts them (one at a time) to new data. …”
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