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Showing 21 - 40 results of 287 for search '(( elements method algorithm ) OR ((( image modeling algorithm ) OR ( data testing algorithm ))))', query time: 0.13s Refine Results
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    Allocating data to multicomputer nodes by physical optimization algorithms for loosely synchronous computations by Mansour, Nashat

    Published 1992
    “…Three optimization methods derived from natural sciences are considered for allocating data to multicomputer nodes. These are simulated annealing, genetic algorithms and neural networks. …”
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    article
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    A multi-class discriminative motif finding algorithm for autosomal genomic data. (c2015) by Wehbe, Gioia Wahib

    Published 2016
    “…Then, it searches for population discriminative motifs or differentiable sequence of SNPs, by implementing Probabilistic Suffix Trees data structures. We initially tested the efficiency and performance of our method on several simulated datasets and then applied it on a real genomic data that has different populations from the Middle East and North Africa (MENA) region. …”
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    masterThesis
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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
    “…The accuracy of these algorithms was assessed with standard statistical measures and ground truth data randomly collected in Prince Edward Island, Canada. …”
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    A Survey of Audio Enhancement Algorithms for Music, Speech, Bioacoustics, Biomedical, Industrial, and Environmental Sounds by Image U-Net by Sania Gul (18272227)

    Published 2023
    “…Different than other published reviews, this review focuses entirely on AE techniques based on image U-Nets. We will discuss the need for AE, U-Net comparison to other DNNs, the benefits of converting the audio to 2D, input representations that are useful for different AE applications, the architecture of vanilla U-Net and the pre-trained models, variations in vanilla architecture incorporated in different E models, and the state-of-the-art AE algorithms based on U-Net in various applications. …”
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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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    A reduced model for phase-change problems with radiation using simplified PN approximations by Belhamadia, Youssef

    Published 2025
    “…The integro-differential equation for the full radiative transfer is replaced by a set of differential equations which are independent of the angle variable and easy to solve using conventional computational methods. To solve the coupled equations, we implement a second-order implicit scheme for the time integration and a mixed finite element method for the space discretization. …”
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    article
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    Image-Based Air Quality Estimation Using Convolutional Neural Network Optimized by Genetic Algorithms: A Multi-Dataset Approach by Arshad Ali Khan (23152516)

    Published 2025
    “…This paper proposes a new approach using convolutional neural networks with genetic algorithms for estimating air quality directly from images. …”
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    Salak Image Classification Method Based Deep Learning Technique Using Two Transfer Learning Models by Theng, Lau Wei

    Published 2022
    “…Deep learning is the most promising algorithm compared to another Machine Learning (ML) algorithm. …”
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    Test time minimization for system-on-chip with test bus assignment and sizin by Harmanani, Haidar M.

    Published 2017
    “…Test access mechanism (TAM) is responsible for test data transport and is characterized by its bandwidth capacity. …”
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    conferenceObject
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    Methodology for Analyzing the Traditional Algorithms Performance of User Reviews Using Machine Learning Techniques by Abdul Karim (417009)

    Published 2020
    “…In this research, different machine-learning algorithms such as logistic regression, random forest and naïve Bayes were tuned and tested. …”
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