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    Optimizing Aircraft Pitch Control Systems: A Novel Approach Integrating Artificial Rabbits Optimizer with PID-F Controller by Abualigah, Laith

    Published 2024
    “…Comparative analysis with various optimization algorithm-based controllers from the literature demonstrates the effectiveness of the proposed technique. …”
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  4. 184
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    Concurrent BIST Synthesis and Test Scheduling Using Genetic Algorithms by Harmanani, H. M.

    Published 2007
    “…The method maximizes concurrent testing of modules while performing the allocation of functional units, test registers, and interconnects. The method is based on a genetic algorithm that efficiently explores the testable design space and finds a sub-optimal test registers assignment for each k-test session. …”
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    article
  6. 186

    Eye-Clustering: An Enhanced Centroids Prediction for K-means Algorithm by Nasser, Youssef

    Published 2024
    “…This work aims to enhance the performance of the K-means algorithm by introducing a novel method for selecting the initial centroids, thereby minimizing randomness and reducing the number of iterations needed to reach optimal results. …”
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    masterThesis
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    An optimization approach for the computation of the minimumdestabilizing uncertainty volume by Al-Sunni, F.M.

    Published 2000
    “…We propose a nonlinear optimization based algorithm for the computation of the stability region for uncertain polynomials. …”
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    article
  9. 189

    Nonlinear Control of Brushless Dual-Fed Induction Generator With a Flywheel Energy Storage System for Improved System Performance by Mohammed Hamidat (3722086)

    Published 2025
    “…In the first stage, a robust Sliding Mode Control (SMC)-based nonlinear decoupled control algorithm is designed to efficiently regulate BDFIG operation. …”
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    Dynamic performance evaluation and machine learning-assisted optimization of a solar-driven system integrated with PCM-based thermal energy storage: A case study approach by Haitham Osman (11737057)

    Published 2025
    “…<p>This paper presents the design, modeling, and multi-objective optimization of an advanced solar energy system based on concentrated solar power technology, aimed at sustainable electricity generation in urban environments. …”
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    A new multiobjective evolutionary algorithm forenvironmental/economic power dispatch by Abido, A.A.

    Published 2001
    “…A new nondominated sorting genetic algorithm (NSGA) based approach is proposed to handle the problem as a true multiobjective optimization problem with competing and noncommensurable objectives. …”
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    article
  13. 193

    A modified ant colony algorithm for evolutionary design of digital circuits by Sait, Sadiq M.

    Published 2003
    “…In this paper, a multiobjective optimization of logic circuits based on a modified ant colony (ACO) algorithm is presented. …”
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  14. 194

    Evolutionary algorithms for state justification in sequential automatic test pattern generation by El-Maleh, Aiman H.

    Published 2005
    “…Evolutionary algorithms have been effective in solving many search and optimization problems. …”
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    article
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    A hybridization of evolution strategies with iterated greedy algorithm for no-wait flow shop scheduling problems by Bilal Khurshid (16715865)

    Published 2024
    “…The ES algorithm begins with a random initial solution and uses an insertion mutation to optimize the solution. …”
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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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  19. 199

    A stochastic iterative learning control algorithm with application to an induction motor by Saab, Samer S.

    Published 2004
    “…A recursive optimal algorithm, based on minimizing the input error covariance matrix, is derived to generate the learning gain matrix of a P-type ILC for linear discrete-time varying systems with arbitrary relative degree. …”
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  20. 200

    Stochastic P-type/D-type iterative learning control algorithms by Saab, Samer S.

    Published 2003
    “…The optimal algorithm is based on minimizing the trace of the input error covariance matrix. …”
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    article