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    Deep Learning-Based Short-Term Load Forecasting Approach in Smart Grid With Clustering and Consumption Pattern Recognition by Dabeeruddin Syed (16864260)

    Published 2021
    “…A k-Medoid based algorithm is employed for clustering whereas the forecasting models are generated for different clusters of load profiles. …”
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    A Modular Reconfigurable Architecture for Asymmetric and Symmetric-key Cryptographic Algorithms by Zaidi, Ali Mustafa

    Published 2007
    “…Numerous such algorithms have been devised, and many have found popularity in different domains. …”
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    masterThesis
  5. 65

    Modified arithmetic optimization algorithm for drones measurements and tracks assignment problem by Abu Zitar, Raed

    Published 2023
    “…In particular, a new modified method based on the Arithmetic Optimization Algorithm is proposed. …”
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  6. 66

    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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    article
  7. 67

    On Higher-Order Iterative Learning Control Algorithm in Presence of Measurement Noise by Saab, Samer S.

    Published 2005
    “…Furthermore, a suboptimal second-order ILC is proposed for a class of nonlinear systems. Based on a numerical example, it is shown that a compatible suboptimal first-order ILC yields better performance than the proposed suboptimal second-order ILC algorithm.…”
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    conferenceObject
  8. 68

    UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data by Behrouz Ahadzadeh (19757022)

    Published 2024
    “…Moreover, the study proposes a hybrid algorithm that combines UniBFS with two filter-based FS methods, ReliefF and Fisher, to identify pertinent features during the global search phase. …”
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    A time-domain algorithm for the analysis of second-harmonicgeneration in nonlinear optical structures by Al-Sunaidi, M. A.

    Published 2000
    “…A time-domain simulator of integrated optical structures containing second-order nonlinearities is presented. The simulation algorithm is based on nonlinear wave equations representing the propagating fields and is solved using the finite-difference time-domain method. …”
    article
  11. 71

    A time-domain algorithm for the analysis of second-harmonicgeneration in nonlinear optical structures by Alsunaidi, M.A.

    Published 2000
    “…A time-domain simulator of integrated optical structures containing second-order nonlinearities is presented. The simulation algorithm is based on nonlinear wave equations representing the propagating fields and is solved using the finite-difference time-domain method. …”
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    article
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    Methodology for Analyzing the Traditional Algorithms Performance of User Reviews Using Machine Learning Techniques by Abdul Karim (417009)

    Published 2020
    “…In this research, different machine-learning algorithms such as logistic regression, random forest and naïve Bayes were tuned and tested. …”
  15. 75

    Minimum UAV fog servers with maximum IoT devices association using genetic algorithms by Abbas, Nadine

    Published 2021
    “…We then propose a heuristic sub-optimal approach based on genetic algorithm (GA) to decide on the minimum number of UAVs to be deployed and the IoT-to-UAV association. …”
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    A three-stage hybrid heuristic algorithm for the capacitated vehicle routing problem. (c2016) by Kfoury, Muhib S.

    Published 2016
    “…We consider heuristic methods that are based on two-phase algorithms. Each such algorithm starts by clustering the underlining network before proceeding into the route construction phase. …”
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    masterThesis
  18. 78

    A hybridization of evolution strategies with iterated greedy algorithm for no-wait flow shop scheduling problems by Bilal Khurshid (16715865)

    Published 2024
    “…To address the complexity of this NP-hard problem, the HES-IG algorithm combines evolution strategies (ES) and iterated greedy (IG) algorithm, as hybridizing algorithms helps different algorithms mitigate their weaknesses and leverage their respective strengths. …”
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    Portfolio Selection Problem Using CVaR Risk Measures Equipped with DEA, PSO, and ICA Algorithms by Abdelouahed Hamdi (14158899)

    Published 2022
    “…It was found that when solving the Mean-CVaR model with evolutionary algorithms, the risk decreased. The efficient boundary of the PSO algorithm was higher than that of the ICA algorithm, and it displayed more efficient portfolios.Therefore, this algorithm was more successful in optimizing the portfolio.…”
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