Showing 1 - 20 results of 365 for search '(((( time modeling algorithm ) OR ( data fitting algorithm ))) OR ( element data algorithm ))', query time: 0.12s Refine Results
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    Time-varying volatility model equipped with regime switching factor: valuation of option price written on energy futures by Leduc, Guillaume

    Published 2025
    “…This paper explores the calculation of European option prices on energy futures using a time-varying volatility model enhanced by a regime switching factor. …”
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    A New Parallel Genetic Algorithm Model by Al-Somani, Turki F.

    Published 2020
    “…This paper presents an implementation of three Genetic Algorithm models for solving a reliability optimization problem for a redundancy system with several failure modes, a modification on a parallel a genetic algorithm model and a new parallel genetic algorithm model. …”
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    A Novel Non-Invasive Estimation of Respiration Rate From Motion Corrupted Photoplethysmograph Signal Using Machine Learning Model by Md. Nazmul Islam Shuzan (16888827)

    Published 2021
    “…The best ML model and the best feature selection algorithm combination were fine-tuned to optimize its performance using hyperparameter optimization. …”
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    Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks by Najam Us Sahar Riyaz (22927843)

    Published 2025
    “…Ensemble schemes such as Gaussian process regression with simple averaging and gradient boosting regressors fortified by permutation feature importance improve robustness in noisy or multi-alloy environments. At the same time, virtual sample augmentation and genetic algorithm feature selection elevate sparse data performance, raising k-nearest neighbor models from R<sup>2</sup> = 0.05 to 0.99 in a representative thiophene set. …”
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    Real-Time Implementation of High Performance Control Scheme for Grid-Tied PV System for Power Quality Enhancement Based on MPPC-SVM Optimized by PSO Algorithm by Abdelbasset Krama (16870008)

    Published 2018
    “…This strategy uses a discrete model of the system based on the time domain to generate the average voltage vector at each sampling period, with the aim of canceling the errors between the estimated active and reactive power values and their references. …”
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    Bird’s Eye View feature selection for high-dimensional data by Samir Brahim Belhaouari (16855434)

    Published 2023
    “…This approach is inspired by the natural world, where a bird searches for important features in a sparse dataset, similar to how a bird search for sustenance in a sprawling jungle. BEV incorporates elements of Evolutionary Algorithms with a Genetic Algorithm to maintain a population of top-performing agents, Dynamic Markov Chain to steer the movement of agents in the search space, and Reinforcement Learning to reward and penalize agents based on their progress. …”
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    Reinforcement R-learning model for time scheduling of on-demand fog placement by Farhat, Peter

    Published 2020
    “…We also demonstrate the ability of our model to improve over time by adapting the new demand of users. …”
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    Improved Transportation Model with Internet of Things Using Artificial Intelligence Algorithm by Ayman Khallel Al-Ani (17541447)

    Published 2023
    “…<p dir="ltr">In this paper, the application of transportation systems in real-time traffic conditions is evaluated with data handling representations. …”
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    A Genetic Algorithm for Improving Accuracy of Software Quality Predictive Models by Azar, Danielle

    Published 2010
    “…In this work, we present a genetic algorithm to optimize predictive models used to estimate software quality characteristics. …”
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    An ant colony optimization algorithm to improve software quality prediction models by Azar, D.

    Published 2011
    “…Objective The objective of this paper is to present an approach that optimizes the accuracy of software quality predictive models when used to classify new data. 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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