Search Results - (( model evaluation drops algorithm ) OR ( identification _ system algorithm ))

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  1. 1
    Musical instrument identification using Convolutional Neural Network (CNN) algorithm / Muhammad Nur Azri Irfan Abdul Rahman

    Musical instrument identification using Convolutional Neural Network (CNN) algorithm / Muhammad Nur Azri Irfan Abdul Rahman by Abdul Rahman, Muhammad Nur Azri Irfan

    Published 2025
    “…Finally, the rigor of evaluation phase is carried out to evaluate the model utilizing precision, recall, F1 score, and the overall accuracy metrics which ascertained robustness and reliability for the model.…”
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  2. 2
    Machine learning methods for herschel-bulkley fluids in annulus: Pressure drop predictions and algorithm performance evaluation

    Machine learning methods for herschel-bulkley fluids in annulus: Pressure drop predictions and algorithm performance evaluation by Kumar, A., Ridha, S., Ganet, T., Vasant, P., Ilyas, S.U.

    Published 2020
    “…This study emphasizes on the performance evaluation of given algorithms and their pitfalls in predicting accurate pressure drop. …”
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  3. 3
    Hybrid model to improve the river streamflow forecasting utilizing multi-layer perceptron-based intelligent water drop optimization algorithm

    Hybrid model to improve the river streamflow forecasting utilizing multi-layer perceptron-based intelligent water drop optimization algorithm by Pham Q.B., Afan H.A., Mohammadi B., Ahmed A.N., Linh N.T.T., Vo N.D., Moazenzadeh R., Yu P.-S., El-Shafie A.

    Published 2023
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  4. 4
    Markov-modulated Bernoulli-based performance analysis for BLUE algorithm under bursty and correlated traffics

    Markov-modulated Bernoulli-based performance analysis for BLUE algorithm under bursty and correlated traffics by Saaidah A.M., Jali M.Z., Marhusin M.F., Abdel-Jaber H.

    Published 2024
    Conference Paper
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  5. 5
    Experimental and modeling evaluation of droplet size in immiscible liquid-liquid stirred vessel using various impeller designs

    Experimental and modeling evaluation of droplet size in immiscible liquid-liquid stirred vessel using various impeller designs by Afshar Ghotli, Reza, Abbasi, Mohammad Reza, Bagheri, AmirHossein, Abdul Raman, Abdul Aziz, Ibrahim, Shaliza, Bostanci, Huseyin

    Published 2019
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  6. 6
    Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah

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

    Published 2015
    “…Empirical cumulative distribution function (CDF) model is presented in evaluating the real traffic distribution. …”
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  7. 7
    Markov-modulated Bernoulli-based Performance Analysis for BLUE Algorithm under Bursty and Correlated Traffics

    Markov-modulated Bernoulli-based Performance Analysis for BLUE Algorithm under Bursty and Correlated Traffics by Saaidah, AM, Jali, MZ, Marhusin, MF, Abdel-Jaber, H

    Published 2024
    “…The MMBP is used to replace the conventional and widely-used Bernoulli process (BP) in evaluating and proposing analytical models based on the BLUE algorithm. …”
    Proceedings Paper
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  8. 8
    Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah

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

    Published 2015
    “…Empirical cumulative distribution function (CDF) model is presented in evaluating the real traffic distribution. …”
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  9. 9
    Multivariable system identification for dynamic discrete-time nonlinear system using genetic algorithm

    Multivariable system identification for dynamic discrete-time nonlinear system using genetic algorithm by Ahmad, R., Jamaluddin, H., Hussain, Mohd Azlan

    Published 2002
    “…The development of a multivariable system identification model for dynamic discrete-time nonlinear system using genetic algorithm was discussed and analysed. …”
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  10. 10
    Benchmark simulator with dynamic environment for job scheduling in grid computing

    Benchmark simulator with dynamic environment for job scheduling in grid computing by Ku-Mahamud, Ku Ruhana

    Published 2014
    “…Characteristics of jobs and resources to be used in evaluating the performance of the scheduling algorithm must reflect the dynamic nature of real grid environment.Static models of jobs and resources cannot be used to generate jobs and resources in simulating the grid environment because of the dynamic nature of the grid.This paper presents a new graph representation of jobs and resources which is practical for hybrid metaheuristic model implementation such as ant colony optimization and genetic algorithm.A dynamic model that can generate jobs and resources similar to the jobs and resources in the real grid environment is also proposed.Jobs and resources may join in or drop out from the grid.Stochastic analysis is performed on the characteristics of jobs and resources.A simulator based on the dynamic expected time to compute, has been developed and can be used as a benchmark.The simulator can generate jobs and resources with the characteristics of jobs and resources in the real grid environment.This will facilitates the evaluation of dynamic job scheduling algorithm.…”
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  11. 11
    Multivariable system identification for dynamic discrete-time nonlinear system using genetic algorithm

    Multivariable system identification for dynamic discrete-time nonlinear system using genetic algorithm by Ahmad, R., Jamaluddin, H., Hussain, M. A.

    Published 2002
    “…The development of a multivariable system identification model for dynamic discrete-time nonlinear system using genetic algorithm was discussed and analysed. …”
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  12. 12
    Adaptive Linear System Identification over Simulated Wireless Environment

    Adaptive Linear System Identification over Simulated Wireless Environment by Elamin, Musab Jabralla Omer Elamin

    Published 2009
    “…The thesis investigates the possibility of performing system identification over wireless network for both on-line and off-line system identification approaches. …”
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  13. 13
    Identification of non-linear dynamic systems using fuzzy system with constrained membership functions

    Identification of non-linear dynamic systems using fuzzy system with constrained membership functions by Yaakob, Mohd. Shafiek

    Published 2004
    “…This study deals with the use of the rule-based fuzzy system for the identification of non-linear dynamic systems. …”
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  14. 14
    Hybrid DE-PEM algorithm for identification of UAV helicopter

    Hybrid DE-PEM algorithm for identification of UAV helicopter by Tijani, Ismaila, Akmeliawati, Rini, Legowo, Ari, Budiyono, Agus, Abdul Muthalif, Asan Gani

    Published 2014
    “…Originality/value – This study presents a novel hybrid algorithm for system identification of an autonomous helicopter model.…”
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  15. 15
    Development of a Universal Artificial Neural Network Model for Pressure Loss Estimation in Pipeline Systems; A comparative Study

    Development of a Universal Artificial Neural Network Model for Pressure Loss Estimation in Pipeline Systems; A comparative Study by Ayoub, Mohammed Abdalla, Demiral, B.M.R

    Published 2010
    “…This study aims to develop a universal artificial neural network model for estimating pressure drop at pipelines under multiphase flow conditions. …”
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  16. 16
    Recursive Subspace Identification Algorithm Using The Propagator Based Method

    Recursive Subspace Identification Algorithm Using The Propagator Based Method by Jamaludin, Irma Wani, Abdul Wahab, Norhaliza

    Published 2017
    “…Hence, it is essential to discover the alternative algorithms in order to apply the concept of subspace identification recursively. …”
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  17. 17
    Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification

    Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification by Abd Samad, Md Fahmi

    Published 2011
    “…Model structure selection is one of the important steps in a system identification process. Evolutionary computation (EC) is known to be an effective search and optimization method and in this paper EC is proposed as a model structure selection algorithm. …”
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  18. 18
    Identification of continuous-time hammerstein system using sine cosine algorithm

    Identification of continuous-time hammerstein system using sine cosine algorithm by E. F., Junis, J. J., Jui, Mohd Helmi, Suid, Mohd Ashraf, Ahmad

    Published 2019
    “…This paper presents the development of identification of continuous-time Hammerstein systems based on Sine Cosine Algorithm (SCA). …”
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  19. 19
    Modified multi-verse optimizer for nonlinear system identification of a double pendulum overhead crane

    Modified multi-verse optimizer for nonlinear system identification of a double pendulum overhead crane by Julakha, Jahan Jui, Mohd Ashraf, Ahmad, Muhammad Ikram, Mohd Rashid

    Published 2021
    “…The experimental findings illustrate that the HMVOSCA algorithm can identify a Hammerstein model that generates an estimated output like the actual DPOC system output. …”
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  20. 20
    Simultaneous Computation of Model Order and Parameter Estimation for System Identification Based on Gravitational Search Algorithm

    Simultaneous Computation of Model Order and Parameter Estimation for System Identification Based on Gravitational Search Algorithm by Kamil Zakwan, Mohd Azmi, Pebrianti, Dwi, Zuwairie, Ibrahim, Shahdan, Sudin, Sophan Wahyudi, Nawawi

    Published 2015
    “…System identification is a technique used to obtain a mathematical model of a system by performing analysis of input-output characteristic of the system. …”
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