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Showing 1 - 19 results of 19 for search '(( algorithm basis function ) OR ((( algorithm python function ) OR ( algorithm fc function ))))*', query time: 0.11s Refine Results
  1. 1
    Radial basis function networks for contingency analysis of bulkpower systems

    Radial basis function networks for contingency analysis of bulkpower systems by Refaee, J.A.

    Published 1999
    “…Radial basis function networks (RBFNs) are used for contingency evaluation of bulk power system. …”
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  2. 2
    A fuzzy basis function network for generator excitation control

    A fuzzy basis function network for generator excitation control by Abido, M.A.

    Published 1997
    “…A fuzzy basis function network (FBFN) based power system stabilizer (PSS) is presented in this paper. …”
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  3. 3
    A novel IoT intrusion detection framework using Decisive Red Fox optimization and descriptive back propagated radial basis function models

    A novel IoT intrusion detection framework using Decisive Red Fox optimization and descriptive back propagated radial basis function models by Osama Bassam J. Rabie (21323741)

    Published 2024
    “…For this purpose, a combination of Decisive Red Fox (DRF) Optimization and Descriptive Back Propagated Radial Basis Function (DBRF) classification are developed in the proposed work. …”
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  4. 4
    BUC algorithm for iceberg cubes

    BUC algorithm for iceberg cubes by Nasr, George E.

    Published 2003
    “…In this paper, we implement the Bottom-Up Computation (BUC) algorithm for computing Iceberg cubes and conduct a sensitivity analysis of BUC with respect to the probability density function of the data. …”
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  5. 5
    Topology design of switched enterprise networks using a fuzzy simulated evolution algorithm

    Topology design of switched enterprise networks using a fuzzy simulated evolution algorithm by Youssef, H.

    Published 2020
    “…The overall cost function has been developed using fuzzy logic. Several variants of the algorithm are proposed and compared together via simulation and experimental results are provided. r 2002 Elsevier Science Ltd. …”
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  6. 6
    Topology design of switched enterprise networks using a fuzzy simulated evolution algorithm

    Topology design of switched enterprise networks using a fuzzy simulated evolution algorithm by Youssef, H.

    Published 2020
    “…The overall cost function has been developed using fuzzy logic. Several variants of the algorithm are proposed and compared together via simulation and experimental results are provided. r 2002 Elsevier Science Ltd. …”
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  7. 7
    Rigorous Phase Equilibrium Calculation Methods for Strong Electrolyte Solutions: The Isothermal Flash

    Rigorous Phase Equilibrium Calculation Methods for Strong Electrolyte Solutions: The Isothermal Flash by Ilias K. Nikolaidis (9217172)

    Published 2022
    “…In this way, an augmented function (Lagrange function) is formulated which serves as the basis for the equations that govern phase equilibrium. …”
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  8. 8
    An Artificial Neural Network for Online Tuning of Genetic Algorithm Based PI Controller for Interior Permanent Magnet Synchronous Motor–Drive

    An Artificial Neural Network for Online Tuning of Genetic Algorithm Based PI Controller for Interior Permanent Magnet Synchronous Motor–Drive by Rahman, M. A.

    Published 2006
    “…In the optimization procedure a performance index is developed to reflect the minimum speed deviation, minimum settling time and zero steady-state error. A radial basis function network (RBFN) is utilized for online tuning of the PI controller parameters to ensure optimum drive performance under different disturbances. …”
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  9. 9
    Android Malware Detection Using Machine Learning

    Android Malware Detection Using Machine Learning by Al Ali, Shaikha

    Published 2024
    “…It was found that SVM using radial basis function (RBF) kernel achieved the highest performance with an accuracy of 99.5%. …”
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  10. 10
    Contingency analysis of bulk power system using neural networks

    Contingency analysis of bulk power system using neural networks by Maghrabi, H.

    Published 1998
    “…Radial basis function networks (RBFNs) are used for the contingency evaluation of bulk power systems. …”
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  11. 11
    Adaptive cooperative control of nonlinear multi-agent systems with uncertain time-varying control directions and dead-zone nonlinearity

    Adaptive cooperative control of nonlinear multi-agent systems with uncertain time-varying control directions and dead-zone nonlinearity by Maryam Shahriari-kahkeshi (17269051)

    Published 2021
    “…Then, by using the dynamic surface control approach and radial-basis function neural network, an adaptive distributed controller is designed for each follower agent. …”
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  12. 12
    A hybrid neuro-fuzzy power system stabilizer for multimachine powersystems

    A hybrid neuro-fuzzy power system stabilizer for multimachine powersystems by Abido, M.A.

    Published 1998
    “…A fuzzy basis function network (FBFN) based power system stabilizer (PSS) is presented in this paper to improve power system dynamic stability. …”
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  13. 13
    Development and Implementation of a Hybrid Intelligent Controller for Interior Permanent Magnet Synchronous Motor Drives

    Development and Implementation of a Hybrid Intelligent Controller for Interior Permanent Magnet Synchronous Motor Drives by Nasir Uddin, M.

    Published 2004
    “…In the optimization procedure a performance index is developed to reflect the minimum speed deviation, minimum settling time and zero steady-state error. A fuzzy basis function network (FBFN) is utilized for online tuning of the PI controller parameters to ensure optimum drive performance under different disturbances. …”
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  14. 14
    Design and performance analysis of hybrid MPPT controllers for fuel cell fed DC-DC converter systems

    Design and performance analysis of hybrid MPPT controllers for fuel cell fed DC-DC converter systems by Shaik Rafikiran (15838929)

    Published 2023
    “…The studied MPPT controllers are Adaptive Adjustable Step-based Perturb and Observe (AASP&O) controllers, Variable Step Value-Radial Basis Function Controller (VSV-RBFC), Adaptive Step Hill Climb (ASHC) based fuzzy technique, Variable P&O with Particle Swarm Optimization (VP&O-PSO), and Variable Step Grey Wolf Algorithm (VSGWA) based fuzzy logic controller. …”
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  15. 15
    Design and performance analysis of hybrid MPPT controllers for fuel cell fed DC-DC converter systems

    Design and performance analysis of hybrid MPPT controllers for fuel cell fed DC-DC converter systems by Shaik, Rafikiran

    Published 2023
    “…The studied MPPT controllers are Adaptive Adjustable Step-based Perturb and Observe (AAS-P&O) controllers, Variable Step Value-Radial Basis Function Controller (VSV-RBFC), Adaptive Step Hill Climb (ASHC) based fuzzy technique, Variable P&O with Particle Swarm Optimization (VP&O-PSO), and Variable Step Grey Wolf Algorithm (VSGWA) based fuzzy logic controller. …”
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  16. 16
    Distinguishing Between Fake and Real Smiles Using EEG Signals and Deep Learning

    Distinguishing Between Fake and Real Smiles Using EEG Signals and Deep Learning by Moussa, Mostafa Mohamed

    Published 2020
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  17. 17
    Wiener-Hammerstein Model Identification-Recursive lgorithms

    Wiener-Hammerstein Model Identification-Recursive lgorithms by Emara-Shabaik, Husam

    Published 2020
    “…These algorithms are derived on the basis of minimizing cost functions of the output errors, the equation errors, and the prediction errors. …”
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  18. 18
    Single-Cell Transcriptome Analysis Highlights a Role for Neutrophils and Inflammatory Macrophages in the Pathogenesis of Severe COVID-19

    Single-Cell Transcriptome Analysis Highlights a Role for Neutrophils and Inflammatory Macrophages in the Pathogenesis of Severe COVID-19 by Hibah Shaath (5599658)

    Published 2020
    “…Further analyses revealed genes associated with the inflammatory response and chemotaxis of myeloid cells, phagocytes, and granulocytes, among the top activated functional categories in BAL from severe COVID-19-affected patients. …”
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  19. 19
    FoGMatch

    FoGMatch by Arisdakessian, Sarhad

    Published 2019
    “…Our solution consists of (1) two optimization problems, one for the IoT devices and one for the fog nodes, (2) preference functions for both the IoT and fog layers to help them rank each other on the basis of several criteria such latency and resource utilization, and (3) centralized and distributed intelligent scheduling algorithms that consider the preferences of both the fog and IoT layers to improve the performance of the overall IoT ecosystem. …”
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