Search Results - (( weibull distribution _ algorithm ) OR ( (parameter OR parameters) estimation force algorithm ))

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  1. 1

    A hybrid intelligent active force controller for robot arms using evolutionary neural networks by Hussein, S.B, Jamaluddin, H, Mailah, M, Zalzala, A.M.S

    Published 2000
    “…In this paper, we propose a hybrid intelligent parameter estimator for the active force control (AFC) scheme which utilizes evolutionary computation (EC) and artificial neural networks (ANN) to control a rigid robot arm. …”
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  2. 2

    Hybrid intelligent active force controller for robot arms using evolutionary neural networks by Hussein, S. B., Jamaluddin, H., Mailah, M., Zalzala, A. M. S.

    Published 2000
    “…In this paper, we propose a hybrid intelligent parameter estimator for the active force control (AFC) scheme which utilizes evolutionary computation (EC) and artificial neural networks (ANN) to control a rigid robot arm. …”
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  3. 3

    Estimation Of Weibull Parameters Using Simulated Annealing As Applied In Financial Data by Hamza, Abubakar

    Published 2023
    “…The finding reveals that the Weibull distribution is well-suited to describing the investment behaviour of the MPS based on the estimates via the SA algorithm. …”
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  4. 4

    Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah by Abdullah, Mohd Azrul

    Published 2015
    “…Analysis results present Weibull Distribution model is the best fitted model. …”
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  5. 5

    Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah by Abdullah, Mohd Azrul

    Published 2015
    “…Analysis results present Weibull Distribution model is the best fitted model. …”
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    Intelligent adaptive active force control of a robotic arm with embedded iterative learning algorithms by Mailah, Musa, Ong, Miaw Yong

    Published 2001
    “…The paper highlights a novel and robust method to control a robotic arm using an iterative learning technique embedded in an active force control strategy. Two main iterative learning algorithms are utilized in the study – the first is used to automatically tune the controller gains while the second to estimate the inertia matrix of the manipulator. …”
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  8. 8

    Non-parametric induction motor rotor flux estimator based on feed-forward neural network by Siti Nursyuhada, Mahsahirun, Nik Rumzi, Nik Idris, Zulkifli, Md. Yusof, Sutikno, Tole

    Published 2022
    “…This estimator is operating without motor parameters and therefore it is independent from parameter uncertainties. …”
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  9. 9

    Adaptive active force control of a robotic arm employing twin iterative learning algorithms / Musa Mailah and Ong Miaw Yong by Mailah, Musa, Ong, Miaw Yong

    Published 2004
    “…The paper highlights a novel and robust method to control a robotic arm using iterative learning technique embedded in an active force control strategy. Two iterative learning algorithms are employed in the study - the first is used to tune automatically the controller gains while the second to estimate the inertia matrix of the robotic arm. …”
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  10. 10

    Competing risks for reliability analysis using Cox’s model by Mohamed Elfaki, Faiz Ahmed, Daud, Isa, Ibrahim, Nor Azowa, Abdullah, M. Y., Usman, Mustofa

    Published 2007
    “…Purpose – Cox’s model with Weibull distribution and Cox’s with exponential distribution are the most important models in reliability analysis. …”
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  11. 11

    An intelligent method to estimate the inertia matrix of a robot arm for active force control using on-line neural network training scheme by Hussein, Shamsul Bahri, Jamaluddin, Hishamuddin, Mailah, Musa

    Published 1999
    “…This paper presents a new intelligent controller algorithm comprising an on-line multi-layer artificial neural network (ANN) training scheme to estimate the inertia matrix of the robot arm to enhance the performance of the active force control (AFC) scheme. …”
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  12. 12

    Crowd behavior monitoring using self-adaptive social force model by Wan Nur Azhani, W. Samsudin, Kamarul Hawari, Ghazali

    Published 2019
    “…The estimated interaction forces of each particle represent the behavior of the crowd, whether it is normal or abnormal. …”
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  13. 13

    Bayesian survival and hazard estimates for Weibull regression with censored data using modified Jeffreys prior by Ahmed, Al Omari Mohammed

    Published 2013
    “…For the Weibull model with right censoring and unknown shape, the full conditional distribution for the scale and shape parameters are obtained via Gibbs sampling and Metropolis-Hastings algorithm from which the survival function and hazard function are estimated. …”
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  14. 14

    Establishment of spectral subtraction-based algorithm for experimental modal analysis under operating condition by Che Ku Eddy Nizwan, Che Ku Husin

    Published 2022
    “…Under the operating condition, the presence of unmeasurable forces causes an error in the transfer function calculation due to incomplete information of input forces. …”
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    Active force control with iterative learning control algorithm for a vehicle suspension by Rosmazi, Rosli

    Published 2013
    “…The new control scheme named active force control with iterative learning control algorithm (AFCIL) is complemented by the classic proportionalintegral-derivative (PID) control incorporated and designed as the outermost control loop. …”
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  17. 17

    Enhancement of impact force determination with modal transformation method by using integration and data filtering /Khoo Shin Yee by Khoo, Shin Yee

    Published 2013
    “…The transformation from high condition number of synthesised FRF matrix to a well-conditioned case is demonstrated by adding additional information of force location. The low quality of fitting a modal model by using modal parameters obtained from the polynomial curve fitting algorithm is highlighted. …”
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  18. 18

    Reduced-rank technique for joint channel estimation in TD-SCDMA systems. by Ismail, Alyani, Sali, Aduwati, Mohd Ali, Borhanuddin, Khatun, Sabira

    Published 2013
    “…Equations for reduced rank-joint channel estimation (JCE) are derived and compared against traditional full rank-joint channel estimators: least square (LS) or Steiner, enhanced LS, and minimum mean square error algorithms. …”
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    Reduced rank technique for joint channel estimation and joint data detection in TD-SCDMA systems by Marzook, Ali Kamil, Ismail, Alyani, Mohd Ali, Borhanuddin, Sali, Aduwati, Khalaf, Mohannad H., Khatun, Sabira

    Published 2013
    “…Equations for reduced rank-joint channel estimation (JCE) are derived and compared against traditional full rank-joint channel estimators: least square (LS) or Steiner, enhanced LS, and minimum mean square error algorithms. …”
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