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    Augmented arithmetic optimization algorithm using opposite-based learning and lévy flight distribution for global optimization and data clustering by Abu Zitar, Raed

    Published 2022
    “…This paper proposes a new data clustering method using the advantages of metaheuristic (MH) optimization algorithms. …”
  3. 43

    Minimizing using BBO and DFO methods by El Zeghondy, Jean

    Published 2022
    “…The goal of this thesis is to develop two MATLAB codes for the numerical algorithm of [1]. To solve nonlinear differential equations we use Runge-Kutta method of fourth order, and for the minimization part, we use two different methods, namely Nelder-Mead and Model Based Descent methods. …”
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    masterThesis
  4. 44

    Optimum Track to Track Fusion Using CMA-ES and LSTM Techniques by Fares, Samar

    Published 2024
    “…An objective function utilizing the covariance of the fused tracks is used by the first algorithm while a cost function based on the Kullback-Leibler (KL) divergence measure is used in the second case for training the LSTM. …”
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    A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method by Amit Kumar Balyan (18288964)

    Published 2022
    “…To deal with the data-imbalance issue, this research develops an efficient hybrid network-based IDS model (HNIDS), which is utilized using the enhanced genetic algorithm and particle swarm optimization(EGA-PSO) and improved random forest (IRF) methods. …”
  7. 47

    Iterative Least Squares Functional Networks Classifier by Faisal, Kanaan A

    Published 2007
    “…Both methodology and learning algorithm for this kind of computational intelligence classifier using the iterative least squares optimization criterion are derived. …”
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    article
  8. 48

    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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    conferenceObject
  9. 49

    Cross entropy error function in neural networks by Nasr, G.E.

    Published 2002
    “…The ANN is implemented using the cross entropy error function in the training stage. …”
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    conferenceObject
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    Distributed optimal coverage control in multi-agent systems: Known and unknown environments by Mohammadhasan Faghihi (22303057)

    Published 2024
    “…The proposed technique offers an optimal solution with a lower cost with respect to conventional Voronoi-based techniques by effectively handling the issue of agents remaining stationary in regions void of information using a ranking function. The proposed approach leverages a novel cost function for optimizing the agents’ coverage and the cost function eventually aligns with the conventional Voronoi-based cost function. …”
  12. 52

    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
    “…<p dir="ltr">The Internet of Things (IoT) is extensively used in modern-day life, such as in smart homes, intelligent transportation, etc. …”
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    Optimum sensors allocation for drones multi-target tracking under complex environment using improved prairie dog optimization by Abu Zitar, Raed

    Published 2024
    “…Since we use Multi-objects to track, the Joint Probability Distribution Function (JPDA) estimates the best measurement values with a preset gating threshold. …”
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  16. 56

    ANT-colony optimization-direct torque control for a doubly fed induction motor : An experimental validation by Said Mahfoud (17150968)

    Published 2022
    “…The new combined ACO-DTC strategy has been studied for optimizing the gains of the PID controller by using a cost function such as Integral Square Error (ISE). …”
  17. 57

    Evolutionary Algorithms for VLSIMultiobjective Netlist Partitioning by Sait, Sadiq M.

    Published 2006
    “…A series of experiments are performed to evaluate the efficiency of the algorithms. ISCAS-85/89 benchmark circuits are used and experimental results are reported and analyzed to compare the performance of GA, TS and SimE. …”
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    article
  18. 58

    Tracking analysis of normalized adaptive algorithms by Moinuddin, M.

    Published 2003
    “…A unified approach is carried out using a mixed-norm-type error nonlinearity. Close agreement between analytical analysis and simulation results is obtained for the case of the NLMS algorithm. …”
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    article
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