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Showing 481 - 500 results of 573 for search '(((( data processing algorithm ) OR ( based learning algorithm ))) OR ( elements data algorithm ))', query time: 0.11s Refine Results
  1. 481
    Using artificial bee colony to optimize software quality estimation models. (c2015)

    Using artificial bee colony to optimize software quality estimation models. (c2015) by Abou Assi, Tatiana Antoine

    Published 2016
    “…We build our model using machine learning techniques in particular rule-based models. …”
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  2. 482
    Performance Analysis of Artificial Neural Networks in Forecasting Financial Time Series

    Performance Analysis of Artificial Neural Networks in Forecasting Financial Time Series by Lasfer, Assia

    Published 2013
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  3. 483
    SDODV. (c2018)

    SDODV. (c2018) by Assi, Maram

    Published 2018
    “…It monitors the traffic load, nodes mobility, neighborhood density and battery power to adjust the routing of packets accordingly. This protocol is based on the distributed reinforcement learning approach and on the traditional AODV. …”
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  4. 484
    Shuffled Linear Regression with Erroneous Observations

    Shuffled Linear Regression with Erroneous Observations by Saab, Samer S.

    Published 2019
    “…Existing methods are either applicable only to data with limited observation errors, work only for partially shuffled data, sensitive to initialization, and/or work only with small dimensions. …”
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  5. 485
    Estimating Bridge Deterioration Age Using Artificial Neural Networks

    Estimating Bridge Deterioration Age Using Artificial Neural Networks by AL HUSSEIN, ASEEL

    Published 2017
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  6. 486
    High-order parametrization of the hypergeometric-Meijer approximants

    High-order parametrization of the hypergeometric-Meijer approximants by Abouzeid M. Shalaby (16329062)

    Published 2023
    “…<p>In this work, we introduce an extension to the hypergeometric algorithm we developed before for the resummation of divergent series.The extension overcome the time-consuming problem we face in the parametrization process of the hypergeometric approximants. …”
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  7. 487
    Optimum Track to Track Fusion Using CMA-ES and LSTM Techniques

    Optimum Track to Track Fusion Using CMA-ES and LSTM Techniques by Fares, Samar

    Published 2024
    “…The first method uses an offline technique based on a global optimizer called the CMA-ES algorithm and the second one uses LSTM in its different forms to learn the online adjustment of the fusion weights between the two tracks. …”
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  8. 488
    Smart non-intrusive appliance identification using a novel local power histogramming descriptor with an improved k-nearest neighbors classifier

    Smart non-intrusive appliance identification using a novel local power histogramming descriptor with an improved k-nearest neighbors classifier by Yassine Himeur (14158821)

    Published 2021
    “…Furthermore, an improved k-nearest neighbors (IKNN) algorithm is presented to reduce the learning computation time and improve the classification performance. …”
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  9. 489
    Mobile Robot Trajectory Tracking Using Neural Networks

    Mobile Robot Trajectory Tracking Using Neural Networks by Mohareri, Omid

    Published 2009
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  10. 490
    Student advising decision to predict student's future GPA based on Genetic Fuzzimetric Technique (GFT)

    Student advising decision to predict student's future GPA based on Genetic Fuzzimetric Technique (GFT) by Kouatli, Issam

    Published 2015
    “…Decision making and/or Decision Support Systems (DSS) using intelligent techniques like Genetic Algorithm and fuzzy logic is becoming popular in many new applications. …”
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  11. 491
    Deep Reinforcement Learning for Resource Constrained HLS Scheduling

    Deep Reinforcement Learning for Resource Constrained HLS Scheduling by Makhoul, Rim

    Published 2022
    “…The two main steps in HLS are: operations scheduling and data-path allocation. In this work, we present a resource constrained scheduling approach that minimizes latency and subject to resource constraints using a deep Q learning algorithm. …”
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  12. 492
    Spatiotemporal Mapping and Monitoring of Mangrove Forests Changes From 1990 to 2019 in the Northern Emirates, UAE Using Random Forest, Kernel Logistic Regression and Naive Bayes Tree Models

    Spatiotemporal Mapping and Monitoring of Mangrove Forests Changes From 1990 to 2019 in the Northern Emirates, UAE Using Random Forest, Kernel Logistic Regression and Naive Bayes Tr... by Elmahdy, Samy

    Published 2020
    “…The approach was developed based on random forest (RF), Kernel logistic regression (KLR), and Naive Bayes Tree machine learning algorithms which use multitemporal Landsat images. …”
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  13. 493
    Predicting long-term type 2 diabetes with support vector machine using oral glucose tolerance test

    Predicting long-term type 2 diabetes with support vector machine using oral glucose tolerance test by Hasan T. Abbas (8115014)

    Published 2019
    “…Using 11 OGTT measurements, we have deduced 61 features, which are then assigned a rank and the top ten features are shortlisted using minimum redundancy maximum relevance feature selection algorithm. All possible combinations of the 10 best ranked features were used to generate SVM based prediction models. …”
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  14. 494
    A Novel Encryption Method for Dorsal Hand Vein Images on a Microcomputer

    A Novel Encryption Method for Dorsal Hand Vein Images on a Microcomputer by M. Z. Yildiz (16855476)

    Published 2019
    “…Second, the pre- and post-processed images were encrypted with a new encryption algorithm in the microcomputer environment. …”
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  15. 495
    Topology and parameter estimation in power systems through inverter-based broadband stimulations

    Topology and parameter estimation in power systems through inverter-based broadband stimulations by Margossian, Harag

    Published 2015
    “…Broadband stimulation signals are injected from distributed generators and their effects are measured at various locations in the grid. To process and evaluate this data, a novel aggregation method based on weighed least squares will be proposed in this study. …”
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  16. 496
    Benchmark on a large cohort for sleep-wake classification with machine learning techniques

    Benchmark on a large cohort for sleep-wake classification with machine learning techniques by Joao Palotti (8479842)

    Published 2019
    “…However, the largest experiments conducted to date, have had only hundreds of participants. In this work, we processed the data of the recently published Multi-Ethnic Study of Atherosclerosis (MESA) Sleep study to have both PSG and actigraphy data synchronized. …”
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  17. 497
    Improving Rule Set Based Software Quality Prediction

    Improving Rule Set Based Software Quality Prediction by Azar, Danielle

    Published 2003
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  18. 498
    Systematic reviews in sentiment analysis: a tertiary study

    Systematic reviews in sentiment analysis: a tertiary study by Alexander Ligthart (14150871)

    Published 2022
    “…In addition to the tertiary study, we also identified recent 112 deep learning-based sentiment analysis papers and categorized them based on the applied deep learning algorithms. …”
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  19. 499
    Identification of the Uncertainty Structure to Estimate the Acoustic Release of Chemotherapeutics From Polymeric Micelles

    Identification of the Uncertainty Structure to Estimate the Acoustic Release of Chemotherapeutics From Polymeric Micelles by Wadi, Ali

    Published 2017
    “…The identified a priori knowledge is used to implement an optimal Kalman filter, a multi-hypothesis Kalman filter, and a variant of the full information estimator (moving horizon estimator) to the problem at hand. The proposed algorithms are initially deployed in a simulation environment, and then the experimental data sets are fed into the algorithms to validate their performance. …”
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  20. 500
    Lagrangian tracking in stochastic fields with application to an ensemble of velocity fields in the Red Sea

    Lagrangian tracking in stochastic fields with application to an ensemble of velocity fields in the Red Sea by Issa, Leila

    Published 2018
    “…Lagrangian tracking of passive tracers in a stochastic velocity field within a sequential ensemble data assimilation framework is challenging due to the exponential growth in the number of particles. …”
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