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Showing 1 - 20 results of 260 for search '(((( algorithm 1 function ) OR ( algorithm cost function ))) OR ( algorithm both function ))', query time: 0.15s Refine Results
  1. 1
    Process Targeting Of Multi-Characteristic Product Using Fuzzy Logic And Genetic Algorithm With An Interval Based Taguchi Cost Function

    Process Targeting Of Multi-Characteristic Product Using Fuzzy Logic And Genetic Algorithm With An Interval Based Taguchi Cost Function by Mujahid, S.N.

    Published 2020
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  2. 2
    Process Targeting Of Multi-Characteristic Product Using Fuzzy Logic And Genetic Algorithm With An Interval Based Taguchi Cost Function

    Process Targeting Of Multi-Characteristic Product Using Fuzzy Logic And Genetic Algorithm With An Interval Based Taguchi Cost Function by Duffuaa, S. O.

    Published 2020
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  3. 3
    Tracking analysis of the NLMS algorithm in the presence of both random and cyclic nonstationarities

    Tracking analysis of the NLMS algorithm in the presence of both random and cyclic nonstationarities by Moinuddin, M.

    Published 2003
    “…Tracking analysis of the normalized least mean square (NLMS) algorithm is carried out in the presence of two sources of nonstationarities: 1) carrier frequency offset between transmitter and receiver; 2) random variations in the environment. …”
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  4. 4
    Synthesis of MVL Functions - Part I: The Genetic Algorithm Approach

    Synthesis of MVL Functions - Part I: The Genetic Algorithm Approach by Sarif, Bambang

    Published 2006
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  5. 5
    Consensus-Based Distributed Formation Control of Multi-Quadcopter Systems: Barrier Lyapunov Function Approach

    Consensus-Based Distributed Formation Control of Multi-Quadcopter Systems: Barrier Lyapunov Function Approach by Nargess Sadeghzadeh-Nokhodberiz (16904952)

    Published 2023
    “…For this purpose, logarithmic BLFs including both the trajectory errors and the errors between the quadcopters’ distances with the desired ones (for the formation goal) are proposed. …”
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  6. 6
    Guaranteed Cost Control Of A Markov Jump Linear Uncertain System UsingA Time-Multiplied Cost Function

    Guaranteed Cost Control Of A Markov Jump Linear Uncertain System UsingA Time-Multiplied Cost Function by Boukas, EK

    Published 2020
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  7. 7
    Guaranteed Cost Control Of A Markov Jump Linear Uncertain System Using A Time-Multiplied Cost Function

    Guaranteed Cost Control Of A Markov Jump Linear Uncertain System Using A Time-Multiplied Cost Function by Boukas, EK

    Published 2020
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  8. 8
    Guaranteed Cost Control Of A Markov Jump Linear Uncertain System Using A Time-Multiplied Cost Function

    Guaranteed Cost Control Of A Markov Jump Linear Uncertain System Using A Time-Multiplied Cost Function by Boukas, EK

    Published 2020
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  9. 9
    Genetic and heuristic algorithms for regrouping service sites. (c2000)

    Genetic and heuristic algorithms for regrouping service sites. (c2000) by Tabbara, Hiba

    Published 2000
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  10. 10
    Design and Implementation of an Advanced Control and Guidance Algorithm of a Single Rotor Helicopter

    Design and Implementation of an Advanced Control and Guidance Algorithm of a Single Rotor Helicopter by Al-Omari, Muhannad A. R. I.

    Published 2013
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  11. 11
    Efficient Algorithms for Constructing Preset Distinguishing Sequences for Nondeterministic Finite State Machines

    Efficient Algorithms for Constructing Preset Distinguishing Sequences for Nondeterministic Finite State Machines by Haddad, Abdul Rahim

    Published 2016
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  12. 12
    Accommodating High Penetrations of Renewable Distributed Generation Mix in Smart Grids

    Accommodating High Penetrations of Renewable Distributed Generation Mix in Smart Grids by Khayata, Mohammad Tarek

    Published 2017
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  13. 13
    Distributed optimal coverage control in multi-agent systems: Known and unknown environments

    Distributed optimal coverage control in multi-agent systems: Known and unknown environments by Mohammadhasan Faghihi (22303057)

    Published 2024
    “…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. …”
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  14. 14
    Optimum Track to Track Fusion Using CMA-ES and LSTM Techniques

    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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  15. 15
    A utility-based algorithm for joint uplink/downlink scheduling in wireless cellular networks

    A utility-based algorithm for joint uplink/downlink scheduling in wireless cellular networks by Saad, Walid

    Published 2012
    “…While most existing literature focuses on downlink-only or uplink-only scheduling algorithms, the proposed algorithm aims at ensuring a utility function that jointly captures the quality of service in terms of delay and channel quality on both links. …”
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  16. 16
    Adaptive Time-Varying Brain Source Localization

    Adaptive Time-Varying Brain Source Localization by Al-Momani, Sajedah A.

    Published 2019
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  17. 17
    Multi-Target Tracking Resources Allocation Using Multi-Agent Modeling and Auction Algorithm

    Multi-Target Tracking Resources Allocation Using Multi-Agent Modeling and Auction Algorithm by De Rochechouart, Maxence

    Published 2023
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  18. 18
    Iterative Least Squares Functional Networks Classifier

    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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  19. 19
    Cross entropy error function in neural networks

    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. The cross entropy function is proven to accelerate the backpropagation algorithm and to provide good overall network performance with relatively short stagnation periods. …”
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  20. 20
    ANT-colony optimization-direct torque control for a doubly fed induction motor : An experimental validation

    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). …”
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