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    Shuffled Linear Regression with Erroneous Observations by Saab, Samer S.

    Published 2019
    “…We propose an optimal recursive algorithm that updates the estimate from the underdetermined function that is based on that permutation-invariant constraint. …”
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    Economic load dispatch using memetic sine cosine algorithm by Abu Zitar, Raed

    Published 2022
    “…As other optimization methods, SCA has main shortcoming in exploitation process when a non-linear constraints problem like ELD is tackled. …”
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    EEG-Based Multi-Modal Emotion Recognition using Bag of Deep Features: An Optimal Feature Selection Approach by Muhammad Adeel Asghar (6724982)

    Published 2019
    “…This paper presents an advanced signal processing method using the deep neural network (DNN) for emotion recognition based on EEG signals. …”
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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
    “…The study employs a time-domain-based objective function to guide the optimization process. …”
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    Stochastic P-type/D-type iterative learning control algorithms by Saab, Samer S.

    Published 2003
    “…This paper presents stochastic algorithms that compute optimal and sub-optimal learning gains for a P-type iterative learning control algorithm (ILC) for a class of discrete-time-varying linear systems. …”
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    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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    Loss Model Control for Efficiency Optimization and Advanced Sliding Mode Controllers with Chattering Attenuation for Five-Phase Induction Motor Drive by Hassen Moussa (19759911)

    Published 2024
    “…<p dir="ltr">This paper proposes firstly a Second Order Sliding Mode Control (SOSMC) based on a Super Twisting Algorithm (STA) (SOSMC-STA) combined with a Direct Field-Oriented Control (DFOC) strategy of a Five-Phase Induction Motor (FPIM). …”
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    On-site workshop investment problem: A novel mathematical approach and solution procedure by Nima Moradi (19418821)

    Published 2023
    “…Next, due to the NP-hardness of the problem, an enhanced Genetic Algorithm (GA)-based metaheuristic with efficient problem-specific improvement rules as local search and effective crossover and mutation operators is proposed. …”
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    Inferential sensing techniques in industrial applications by Shakil,, Muhammad

    Published 0007
    “…System delays are obtained by approximating the model by a linear model. Genetic algorithm, which is a heuristic optimization technique, is used to ¯nd the system delays of the linear model, which are used in dynamical neural network model. …”
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    Uplink Noma in UAV-Assisted IoT Networks by Mrad, Ali

    Published 2022
    “…The second device is then selected using a heuristic algorithm based on prioritizing devices with higher bit rate requirements and strict deadlines. …”
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    Development of multivariable PID controller gains in presence of measurement noise by Saab, Samer S.

    Published 2017
    “…The development of the proposed optimal algorithm is based on minimising a stochastic performance index in presence of erroneous initial conditions, white measurement noise, and white process noise. …”
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    MoveSchedule by Zouein, Pierette

    Published 1995
    “…The layout construction algorithm that underlies MoveSchedule uses Constraint Satisfaction to find the set of all positions that meet the constraints on resources' positions and Linear Programming to find the optimal positions that minimize resource transportation and relocation costs. …”
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    masterThesis
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    LDSVM: Leukemia Cancer Classification Using Machine Learning by Abdul Karim (417009)

    Published 2022
    “…The main aim was to predict the initial leukemia disease. Machine learning algorithms such as decision tree (DT), naive bayes (NB), random forest (RF), gradient boosting machine (GBM), linear regression (LinR), support vector machine (SVM), and novel approach based on the combination of Logistic Regression (LR), DT and SVM named as ensemble LDSVM model. …”
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    From Collatz Conjecture to chaos and hash function by Masrat Rasool (17807813)

    Published 2023
    “…<p>The non-linear property of Chaos is a promising approach to information security, and many accomplishments have been made by combining Chaos with several sub-security domains, including chaos-based stream ciphers, block ciphers, image encryption, and hash functions. …”