Showing 1 - 20 results of 799 for search '(((( implement modeling algorithm ) OR ( relevant data algorithm ))) OR ( data using algorithms ))', query time: 0.21s Refine Results
  1. 1

    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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    article
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    Auto-indexing Arabic texts based on association rule data mining. (c2015) by Rouba G. Nasrallah

    Published 2015
    “…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
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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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    article
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    Indexing Arabic texts using association rule data mining by Haraty, Ramzi A.

    Published 2019
    “…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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    article
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    Efficient Approximate Conformance Checking Using Trie Data Structures by Awad, Ahmed

    Published 2021
    “…By encoding the proxy behavior using a trie data structure, we obtain a logarithmically reduced search space for alignment computation compared to a set-based representation. …”
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    Allocation and re-allocation of data in a grid using an adaptive genetic algorithm by Mansour, N.

    Published 2006
    “…Allocation and re-allocation of data in a grid using an adaptive genetic algorithm. …”
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    conferenceObject
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    The automation of the development of classification models and improvement of model quality using feature engineering techniques by Sjoerd Boeschoten (17347045)

    Published 2023
    “…The framework allows practitioners and researchers to automatically generate different classification models. This research used High-Resolution Orbitrap-based Mass Spectrometers (HRMS) data to create automated prediction models for the first time in literature. …”
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    Parameter identification of PV solar cells and modules using bio dynamics grasshopper optimization algorithm by Mostafa Jabari (21841727)

    Published 2024
    “…The subsequent sections of the paper delve into the intricacies of the PV cell and module model, articulate the formulation of the proposed algorithm, present simulations, and analyse the obtained results. …”
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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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    Using Machine Learning Algorithms to Forecast Solar Energy Power Output by Ali Jassim Lari (22597940)

    Published 2025
    “…We focused on the first 30-min, 3-h, 6-h, 12-h, and 24-h windows to gain an appreciation of the impact of forecasting duration on the accuracy of prediction using the selected machine learning algorithms. The study results show that Random Forest outperformed all other tested algorithms. …”
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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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    Limiting the Collection of Ground Truth Data for Land Use and Land Cover Maps with Machine Learning Algorithms by Usman Ali (6586886)

    Published 2022
    “…This was accomplished by (1) extracting reliable LULC information from Sentinel-2 and Landsat-8 s images, (2) generating remote sensing indices used to train ML algorithms, and (3) comparing the results with ground truth data. …”