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  1. 1

    Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach by Nurnajmin Qasrina Ann, ., Pebrianti, Dwi, Mohamad Fadhil, Abas, Bayuaji, Luhur

    Published 2022
    “…Therefore, it is crucial to assess the parameter of chaotic systems. To solve the issue of parameter estimation for a chaotic system, deep learning is utilized. …”
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    Conference or Workshop Item
  2. 2

    LASSO-type estimations for threshold autoregressive and heteroscedastic time series models. by Muhammad Jaffri Mohd Nasir

    Published 2020
    “…To consistently estimate relevant thresholds from the threshold set obtained by the group LASSO, the backward elimination algorithm (BEA) is utilized. …”
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    UMK Etheses
  3. 3

    Simultaneous computation of model order and parameter estimation for ARX model based on single swarm and multi swarm simulated Kalman filter by Kamil Zakwan, Mohd Azmi, Zuwairie, Ibrahim, Pebrianti, Dwi, Mohd Saberi, Mohamad

    Published 2017
    “…Simultaneous Model Order and Parameter Estimation (SMOPE) and Simultaneous Model Order and Parameter Estimation based on Multi Swarm (SMOPE-MS) are two techniques of implementing meta-heuristic algorithm to iteratively establish an optimal model order and parameters simultaneously for an unknown system. …”
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    Article
  4. 4

    Estimation of photovoltaic models using an enhanced Henry gas solubility optimization algorithm with first-order adaptive damping Berndt-Hall-Hall-Hausman method by Ramachandran, Murugan, Sundaram, Arunachalam, Ridha, Hussein Mohammed, Mirjalili, Seyedali

    Published 2024
    “…Then in terms of methodology, the Enhanced Henry Gas Solubility Optimization (EHGSO) algorithm is combined with the Sine-Cosine mutualism phase of Symbiotic Organisms Search (SOS) for efficiently estimating the unknown parameters of PV models. …”
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    Article
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    Augmented model based double iterative loop techniques for integrated system optimisation and parameter estimation of large scale industrial processes by Normah Abdullah, Brdys, M.A., Roberts, P.D.

    Published 1993
    “…The methods incorporate integrated system optimisation and parameter estimation which utilizes process measurements to achieve real process optimality inspite of model reality differences. …”
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    Article
  7. 7

    Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh by Rawaa Dawoud Hassan, Al-Dabbagh

    Published 2015
    “…The simulation results show the effectiveness of the ARDE method over other conventional techniques, transcending the limits of the existing state-of-the-art algorithms in estimating the parameters of robot. …”
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    Thesis
  8. 8

    Simultaneous Computation of Model Order and Parameter Estimation for Arx Model Based on Multiswarm Particle Swarm Optimization by Kamil Zakwan, Mohd Azmi, Zuwairie, Ibrahim

    Published 2015
    “…Simultaneous Model Order and Parameter Estimation (SMOPE) is a method of utilizing meta-heuristic algorithm to iteratively determine an optimal model order and parameters simultaneously for an unknown system. …”
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    Article
  9. 9

    Advanced online battery states coestimation using Kalman filter for electric vehicle Applications / Prashant Shrivastava by Prashant , Shrivastava

    Published 2021
    “…In addition to co-estimation of SOC and SOE in the first method, the SOP estimation is performed by using identified Rint battery model parameters using the forgetting factor recursive least square (FFRLS) algorithm. …”
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    Thesis
  10. 10

    The computation of confidence intervals for the state parameters of power systems by Khan, Z., Razali, R.B., Daud, H., Nor, N.M., Fotuhi-Firuzabad, M., Krebs, K.L.

    Published 2016
    “…The statistical assumptions of the measurement errors have been utilized to characterize the probabilistic behavior of the estimated parameters in terms of confidence intervals. …”
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    Article
  11. 11

    The computation of confidence intervals for the state parameters of power systems by Khan, Z., Razali, R.B., Daud, H., Nor, N.M., Fotuhi-Firuzabad, M., Krebs, K.L.

    Published 2016
    “…The statistical assumptions of the measurement errors have been utilized to characterize the probabilistic behavior of the estimated parameters in terms of confidence intervals. …”
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    Article
  12. 12

    Restoration of blurred images using geometric and chebichef moments / Ahlad Kumar by Ahlad, Kumar

    Published 2016
    “…In the third method, Tchebichef moments (TM) of low order are selected as features used as inputs to ELM to estimate the Gaussian blur parameters. Once the blur parameters are estimated, image restoration of the proposed method is carried out using split Bregman algorithm. …”
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    Thesis
  13. 13

    Predictive modelling of machining parameters of S45C mild steel by Abbas, Adnan Jameel

    Published 2016
    “…This research adopts the utilization of three types of heurestic algorithms to achieve the minimization operation; Genetic Algorithm (GA). …”
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    Thesis
  14. 14

    Individual-tree segmentation and extraction based on LiDAR point cloud data by Liu, Xiaofeng, Abdullah, Muhamad Taufik, Mustaffa, Mas Rina, Nasharuddin, Nurul Amelina

    Published 2024
    “…Utilizing LiDAR point cloud data and ground-measured data from 30 plots, we examined the sensitivity of individual tree segmentation to key parameters by varying the grid values of the point cloud distance discriminant clustering algorithm and adjusting the canopy height resolution (CHR) of the watershed algorithm. …”
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    Article
  15. 15

    Identifying high influence parameters using Genetic Algorithm (GA) chromosomes for water consumption by Siti Arpah, Ahmad, Nurul Nadia Hani, ., Ahmad Firdaus, Ahmad Fadzil, Nor Elaiza, Abd Khalid, Rosanita, Adnan, Khairul Anwar, Rasmani, Wan Isni Sofiah, Wan Din

    Published 2021
    “…However, monitoring water consumption from household usage is tedious and time consuming. This work utilized Genetic Algorithm (GA) to optimize the coefficient of micro-components of water consumption (CMWC) values to determine high influential household routine parameters. …”
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    Article
  16. 16

    Application of image processing and adaptive neuro-fuzzy system for estimation of the metallurgical parameters of a flotation process by Jahedsaravani, A., Massinaei, Mohammad, Marhaban, Mohammad Hamiruce

    Published 2016
    “…The authors have already developed some reliable algorithms for measurement of the froth surface visual parameters such as bubble size distribution, froth color, velocity and stability. …”
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    Article
  17. 17

    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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    Article
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    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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    Article
  20. 20

    A Novel Approach to Estimate Diffuse Attenuation Coefficients for QuickBird Satellite Images: A Case Study at Kish Island, the Persian Gulf. by Pradhan, Biswajeet, Mohd Shafri, Helmi Zulhaidi, Mansor, Shattri, Kabiri, Keivan, Samim-Namin, Kaveh

    Published 2013
    “…Since the aforementioned algorithm has been developed for other types of sensors, an approach using weighted mean value of parameters for SeaWiFS, MERIS, VIIRS, and OCTS sensors were employed to estimate parameter values for QuickBird image. …”
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    Article