Showing 1 - 13 results of 13 for search '(((( algorithm cep function ) OR ( algorithm side functions ))) OR ( algorithm python function ))', query time: 0.10s Refine Results
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    ANT-colony optimization-direct torque control for a doubly fed induction motor : An experimental validation by Said Mahfoud (17150968)

    Published 2022
    “…For that reason, this work is focused on the theoretical studies and experimental validation on dSPACE Board DS1104 of the new proposed approach based on PID speed regulation, optimized by the Ant Colony Optimization algorithm (ACO) for DTC, applied to both sides of the Doubly Fed Induction Motor (DFIM), to overcome the previous drawbacks cited at the beginning. …”
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    Simultaneous stabilization of multimachine power systems viagenetic algorithms by Abdel-Magid, Y.L.

    Published 1999
    “…The problem of selecting the parameters of power system stabilizers which simultaneously stabilize this set of plants is converted to a simple optimization problem which is solved by a genetic algorithm with an eigenvalue-based objective function. …”
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    article
  4. 4

    Evolutionary algorithm for predicting all-atom protein structure by Mansour, Nashat

    Published 2011
    “…This algorithm produces a 3D structure of the whole protein, including back-bone and side-chain atoms, by minimizing the energy function associated with the structure. …”
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    conferenceObject
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    Genetic Algorithm Based Simultaneous Eigenvalue Placement Of Power Systems by Abdel Magid, Y.L.

    Published 2020
    “…The task of selecting the output feedback gains is converted to a simple optimization problem with an eigenvaluebased objective function, which is solved by a genetic algorithm. An objective function is presented allowing the selection of the output feedback gains to place the closed-loop eigenvalues in the left-hand side of a vertical line in the complex s-plane while shifting a specific mode of oscillation to a vertical strip and with bounds on the damping ratio. …”
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    article
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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
    “…<p dir="ltr">This paper proposes a high performance control scheme for a double function grid-tied double-stage PV system. It is based on model predictive power control with space vector modulation. …”
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    Power system output feedback stabilizer design via geneticalgorithms by Abdel-Magid, Y.L.

    Published 1997
    “…Two methods are presented: in the first method, the problem is formulated as an optimization problem with a standard infinite time quadratic objective function. A digital simulation of the power system is then used in conjunction with the genetic algorithm to determine the output feedback gains. …”
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    Fragment-based computational protein structure prediction by Mansour, Nashat

    Published 2014
    “…The method is based on a two-phase Scatter Search algorithm that minimizes the energy function. Backbone fragments are extracted from the Robetta server and side chains are, extracted from the Dunbrack Library. …”
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    conferenceObject
  9. 9

    Robust tuning of power system stabilizers in multimachine powersystems by Abdel-Magid, Y.L.

    Published 2000
    “…The problem of selecting the stabilizer parameters is converted to a simple optimization problem with an eigenvalue-based objective function, which is solved by a tabu search algorithm. …”
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    article
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    Fragment based protein structure prediction. (c2013) by Terzian, Meghrig Ohanes

    Published 2016
    “…The method is based on a two-phase Scatter Search metaheuristic that minimizes the energy function. Backbone fragments selections extracted from the Robetta server are followed by side chain selections, extracted from the Dunbrack Library. …”
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    masterThesis
  11. 11

    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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    masterThesis
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