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  1. 1
    Parallel distributed genetic algorithm development based on microcontrollers framework

    Parallel distributed genetic algorithm development based on microcontrollers framework by Krishnan P.S., Kiong T.S., Koh J.

    Published 2023
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  2. 2
    PSO and Linear LS for parameter estimation of NARMAX/NARMA/NARX models for non-linear data / Siti Muniroh Abdullah

    PSO and Linear LS for parameter estimation of NARMAX/NARMA/NARX models for non-linear data / Siti Muniroh Abdullah by Abdullah, Siti Muniroh

    Published 2017
    “…Results suggest that the PSO algorithm is viable alternative to other established algorithms for LLS parameter estimation. …”
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  3. 3
    Improvement Of Local-Based Stereo Vision Disparity Map Estimation Algorithm

    Improvement Of Local-Based Stereo Vision Disparity Map Estimation Algorithm by Hamzah, Rostam Affendi

    Published 2017
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  4. 4
    Optimal parameter estimation of permanent magnet synchronous motor by using Mothflame optimization algorithm / Abdolmajid Dejamkhooy and Sajjad Asefi

    Optimal parameter estimation of permanent magnet synchronous motor by using Mothflame optimization algorithm / Abdolmajid Dejamkhooy and Sajjad Asefi by Dejamkhooy, Abdolmajid, Asefi, Sajjad

    Published 2018
    “…For this purpose, optimal parameter estimation problem is constructed as a least squares one. …”
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  5. 5
    Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach

    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
    “…After that, it has been suggested to improve the efficiencies in the Deep Neural Network (DNN) model by combining the DNN with an unsupervised machine learning algorithm, the K-Means clustering algorithm. This study constructs the flow of DNN based method with the K-Means algorithm. …”
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  6. 6
    Combination of Minimum-Maximum (M-M) Attribute and Zero-INTENS-Difference (Z-I-D) Attribute for Estimating Seismically Thin-Bed Thickness

    Combination of Minimum-Maximum (M-M) Attribute and Zero-INTENS-Difference (Z-I-D) Attribute for Estimating Seismically Thin-Bed Thickness by Purnomo, Eko Widi, Harith, Zuhar Zahir Tuan

    Published 2011
    “…Bad thickness estimation is resulted for 20% noise seismic. The method algorithm is extended for similar dipole polarity model and multilayer model to bring the method to real seismic data nearer. …”
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  7. 7
    Parallel visualization approach of a 3D heart model

    Parallel visualization approach of a 3D heart model by Malekpour, A., Ling, T.C., Lim, W.C.

    Published 2008
    “…The main target of this paper is to find an optimum strategy for the construction of the RF map and a decent estimation algorithm. …”
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  8. 8
    Risk assessment for safety and health algorithm for building construction in Oman

    Risk assessment for safety and health algorithm for building construction in Oman by Al-Anbari, Saud Said

    Published 2015
    “…This common mistake has cost and time implications in construction activities. It was found that 60% of evaluations using RA might be estimated mistakenly. …”
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  9. 9
    The computation of confidence intervals for the state parameters of power systems

    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
    “…Conclusions: The results of the study show that the method is effective and practically applicable in the state estimation of a power system. …”
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  10. 10
    The computation of confidence intervals for the state parameters of power systems

    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
    “…Conclusions: The results of the study show that the method is effective and practically applicable in the state estimation of a power system. …”
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  11. 11
    A comprehensive fault location estimation using voltage sag profile for non-homogenous distribution networks

    A comprehensive fault location estimation using voltage sag profile for non-homogenous distribution networks by Mokhlis, Hazlie, Li, H.Y., Mohamad, H., Bakar, A.H.A.

    Published 2010
    “…The uncertainty of fault resistance is also considered in this method by constructing the voltage sag equations bayed on different fault resistance values. …”
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  12. 12
    Applying machine learning and particle swarm optimization for predictive modeling and cost optimization in construction project management

    Applying machine learning and particle swarm optimization for predictive modeling and cost optimization in construction project management by almahameed, Bader aldeen, Bisharah, Majdi

    Published 2024
    “…Particle Swarm Optimization (PSO) has demonstrated its efficacy in addressing the issue of construction waste reduction and enhancing the accuracy of cost estimation through the identification of optimal combinations of variables. …”
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  13. 13
    k- Nearest Neighbor Algorithm For Improving Accuracy In Clutter Based Location Estimation Of Wireless Nodes

    k- Nearest Neighbor Algorithm For Improving Accuracy In Clutter Based Location Estimation Of Wireless Nodes by Muhammad Mansoor Alam, Mazliham Mohd Su'ud, Patrice Boursier, Shahrulniza Musa

    Published 2013
    “…This research is focusing on the precise location estimation of mobile node by using k - nearest neighbor algorithm (k-NN). …”
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  14. 14
    Reproducing kernel Hilbert space method for cox proportional hazard model

    Reproducing kernel Hilbert space method for cox proportional hazard model by Abdul Manaf, Nur'azah

    Published 2016
    “…Then, we apply the kernel method to the survival data. Finally, we propose an algorithm of minimization of the loss function in the general Cox model. …”
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  15. 15
    Nonlinear least squares parameter estimation problem using Levenberg-Marquardt method

    Nonlinear least squares parameter estimation problem using Levenberg-Marquardt method by Kaw, Wei Ching, Kek, Sie Long, Sim, Sy Yi

    Published 2017
    “…Least squares method, which is a statistical method with minimum sum squares of errors (SSE), is used for curve fitting and parameter estimation. …”
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  16. 16
    Estimation Of Time Of Concentration Using Triangulated Irregular Network Method

    Estimation Of Time Of Concentration Using Triangulated Irregular Network Method by Ewe, Teik Tsia

    Published 2015
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  17. 17
    Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari

    Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari by Satari, Siti Zanariah

    Published 2015
    “…In this study, we propose an alternative method of constructing a confidence interval based from the distribution of the estimated value of error concentration parameter obtained from the Fisher information matrix. …”
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  18. 18
    Non-regularized reconstruction of magnetic moment distribution of magnetic nanoparticles using barnacles mating optimizer

    Non-regularized reconstruction of magnetic moment distribution of magnetic nanoparticles using barnacles mating optimizer by Mohd Mawardi, Saari, Mohd Herwan, Sulaiman, Nurul Akmal, Che Lah, Mohd Razali, Daud, Kiwa, Toshihiko

    Published 2023
    “…A reconstruction comparison among the BMO, Particle Swarm (PSO), Genetic Algorithm (GA), Sine Cosine Algorithm (SCA) optimizers, and NNLS method is presented. …”
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  19. 19
    Integrated applications of building information modeling in project cost management: a systematic review

    Integrated applications of building information modeling in project cost management: a systematic review by M. Farouk, Abdelrahman, Rahimi, A. Rahman

    Published 2023
    “…On the contrary, integrated approaches for cost estimation include integration with cost-plus pricing, discrepancy analysis, construction progress curves, estimation standards, algorithms, declarative mappings, life cycle sustainability assessment, ontology, Web-based frameworks and structured query language. …”
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  20. 20
    Development of a hybrid PSO-ANN model for estimating glucose and xylose yields for microwave-assisted pretreatment and the enzymatic hydrolysis of lignocellulosic biomass

    Development of a hybrid PSO-ANN model for estimating glucose and xylose yields for microwave-assisted pretreatment and the enzymatic hydrolysis of lignocellulosic biomass by Mohammad, Saleem Ethaib, Omar, Rozita, Mustapa Kamal, Siti Mazlina, Awang Biak, Dayang Radiah, S., Syafiie

    Published 2018
    “…The PSO algorithm suggested an optimum number of neurons in the hidden layer as 15 and a learning rate of 0.761 these consequently used to construct the ANN model. …”
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