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Showing 1 - 20 results of 836 for search '(((( data using algorithm ) OR ( based machine algorithm ))) OR ( element update algorithm ))', query time: 0.15s Refine Results
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    Multimodal EEG and Keystroke Dynamics Based Biometric System Using Machine Learning Algorithms by Arafat Rahman (8065562)

    Published 2021
    “…We also developed a binary template matching-based algorithm, which gives 93.64% accuracy 6X faster. …”
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    Methodology for Analyzing the Traditional Algorithms Performance of User Reviews Using Machine Learning Techniques by Abdul Karim (417009)

    Published 2020
    “…<p dir="ltr">Android-based applications are widely used by almost everyone around the globe. …”
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    Using machine learning algorithm for detection of cyber-attacks in cyber physical systems by Almajed, Rasha

    Published 2022
    “…There are a variety of ways in which AI technology can aid in the growth and profitability of a variety of industries. Such data can be parsed using ML and AI approaches in designed to check attacks on CPSs. …”
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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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    Power System Transient Stability Assessment Based on Machine Learning Algorithms and Grid Topology by Senyuk, Mihail

    Published 2023
    “…In this study, the emergency control algorithms based on ensemble machine learning algorithms (XGBoost and Random Forest) were developed for a low-inertia power system. …”
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    article
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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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    Wild Blueberry Harvesting Losses Predicted with Selective Machine Learning Algorithms by Humna Khan (17541972)

    Published 2022
    “…The performance of three machine learning (ML) algorithms was assessed to predict the wild blueberry harvest losses on the ground. …”
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    Optimization of Interval Type-2 Fuzzy Logic System Using Grasshopper Optimization Algorithm by Saima Hassan (14918003)

    Published 2022
    “…The antecedent part parameters (Gaussian membership function parameters) are encoded as a population of artificial swarm of grasshoppers and optimized using its algorithm. Tuning of the consequent part parameters are accomplished using extreme learning machine. …”
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    A Novel Genetic Algorithm Optimized Adversarial Attack in Federated Learning for Android-Based Mobile Systems by Faria Nawshin (21841598)

    Published 2025
    “…<p dir="ltr">Federated Learning (FL) is gaining traction in Android-based consumer electronics, enabling collaborative model training across decentralized devices while preserving data privacy. However, the increasing adoption of FL in these devices exposes them to adversarial attacks that can compromise user data and device security. …”
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    Predicting Plasma Vitamin C Using Machine Learning by Daniel Kirk (17302798)

    Published 2022
    “…The objective of this study is to predict plasma vitamin C using machine learning. The NHANES dataset was used to predict plasma vitamin C in a cohort of 2952 American adults using regression algorithms and clustering in a way that a hypothetical health application might. …”
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    Using genetic algorithms to optimize software quality estimation models by Azar, Danielle

    Published 2004
    “…Hence, the accuracy of the models often deteriorates significantly when they are used to classify new data. This thesis explores the use of genetic algorithms for the problem of optimizing existing rule-based software quality estimation models. …”
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    masterThesis
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    Ensemble-Based Spam Detection in Smart Home IoT Devices Time Series Data Using Machine Learning Techniques by Ameema Zainab (16864263)

    Published 2020
    “…A spamicity score was awarded to each of the IoT devices by the algorithm, based on the feature importance and the root mean square error score of the machine learning models to determine the trustworthiness of the device in the home network. …”