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  1. 1
    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. In the next step, the parameter identification as an optimization problem is solved by Moth-flame optimization, which is a novel nature-inspired heuristic algorithm. …”
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  2. 2
    Sediment load forecasting from a biomimetic optimization perspective: Firefly and Artificial Bee Colony algorithms empowered neural network modeling in �oruh River

    Sediment load forecasting from a biomimetic optimization perspective: Firefly and Artificial Bee Colony algorithms empowered neural network modeling in �oruh River by Katipo?lu O.M., Kartal V., Pande C.B.

    Published 2025
    “…The hybrid model is a novel approach for estimating sediment load based on various input variables. …”
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  3. 3
    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
    “…Here, we introduce a measure of similarity based on the circular distance and obtain a cluster tree using the single linkage clustering algorithm. …”
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  4. 4
    Comparing three methods of handling multicollinearity using simulation approach

    Comparing three methods of handling multicollinearity using simulation approach by Adnan, Norliza

    Published 2006
    “…RR on the other hand is the modified least square method that allows a biased but more precise estimator. …”
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  5. 5
    A Comparative Study On Some Methods For Handling Multicollinearity Problems

    A Comparative Study On Some Methods For Handling Multicollinearity Problems by Adnan, Norliza, Ahmad, Maizah Hura, Adnan, Robiah

    Published 2006
    “…RR on the other hand is the modified least square method that allows a biased but more precise estimator. …”
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  6. 6
    Speed sensorless control for PMSM drives using Extended Kalman Filter

    Speed sensorless control for PMSM drives using Extended Kalman Filter by Mat Lazi, Jurifa, Nordin, Mohamad Ikhwan, Talib, Md Hairul Nizam, Ibrahim, Zulkifilie

    Published 2021
    “…Therefore, this project proposes sensorless control using an EKF. This method provides an optional estimation algorithm for the non-linear system that can produce a fast and accurate estimation of state variables. …”
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  7. 7
    A comparative study on some methods for handling multicollinearity problems

    A comparative study on some methods for handling multicollinearity problems by Adnan, Norliza, Ahmad, Maizah Hura, Adnan, Robiah

    Published 2006
    “…RR on the other hand is the modified least square method that allows a biased but more precise estimator. …”
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  8. 8
    The effectiveness of debt rule on fiscal sustainability: do macroeconomic data matter?

    The effectiveness of debt rule on fiscal sustainability: do macroeconomic data matter? by Cahyadin, Malik, Sarmidi, Tamat, Khalid, Norlin, Siong, Hook Law

    Published 2023
    “…There are two existing indicators are widely utilized cover primary gap and recursive algorithm. To deal with the potential of a random walk of the variables, the two-step system generalized method of moment (GMM) estimator is employed. …”
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  9. 9
    Estimated and analysis of the relationship between the endogenous and exogenous variables using fuzzy semi-paranetric sample selection model

    Estimated and analysis of the relationship between the endogenous and exogenous variables using fuzzy semi-paranetric sample selection model by MuhamadSafiih, L, Kamil, A.A., Abu Osman, M.T.

    Published 2014
    “…An algorithm using the concept of fuzzy modelling is developed. …”
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  10. 10
    Input Information in the Approximate Calculation of Two-Dimensional Integral from Highly Oscillating Functions (Irregular Case)

    Input Information in the Approximate Calculation of Two-Dimensional Integral from Highly Oscillating Functions (Irregular Case) by Lytvyn, Oleg M., Nechuiviter, Olesia, Pershyna, Iuliia, Mezhuyev, Vitaliy

    Published 2019
    “…Current stage of research in astronomy, radiology, computed tomography, holography, and radar is characterized by broad use of digital technologies, algorithms, and methods. …”
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  11. 11
    Operational matrix based on Genocchi polynomials for solution of delay differential equations

    Operational matrix based on Genocchi polynomials for solution of delay differential equations by Isah, Abdulnasir, Phang, Chang

    Published 2017
    “…In this paper, we present a new simple and effective algorithm for solving generalized Pantograph equa-tions, delay differential equations with neutral terms and delay differential system with constant and variable coefficients.The new method is based on one of the Appell polynomials, namely Genocchi poly-nomials. …”
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  12. 12
    Proving the efficiency of alternative linear regression model based on mean square error (MSE) and average width using aquaculture data

    Proving the efficiency of alternative linear regression model based on mean square error (MSE) and average width using aquaculture data by Awang Nawi, Mohamad Arif, Wan Ahmad, Wan Muhamad Amir, Mohd Ibrahim, Mohamad Shafiq, Mamat, Mustafa, Khamis, Mohd Fahdli, Mohamed, Mohamad Afendee

    Published 2019
    “…The main objective of this paper is to compare mean square error (MSE) and the average width between alternative linear regression models and linear regression model. The alternative method in this study is a combination of four methods, namely multiple linear regression method, the bootstrap method, a robust regression method and fuzzy regression through the construction of algorithms by using SAS software. …”
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  13. 13
    Proving the eficiency of Alternative Linear regression Model Based on Mean Square Error (MSE) and average width using aquaculture data

    Proving the eficiency of Alternative Linear regression Model Based on Mean Square Error (MSE) and average width using aquaculture data by Awang Nawi, Mohamad Arif, Wan Ahmad, Wan Muhamad Amir, Mohd Ibrahim, Mohamad Shafiq, Mamat, Mustafa, Khamis, Mohd Fadhli, Mohamed, Mohamad Afendee

    Published 2019
    “…The main objective of this paper is to compare mean square error (MSE) and the average width between alternative linear regression models and linear regression model. The alternative method in this study is a combination of four methods, namely multiple linear regression method, the bootstrap method, a robust regression method and fuzzy regression through the construction of algorithms by using SAS software. …”
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  14. 14
    An optimized ensemble for predicting reservoir rock properties in petroleum industry

    An optimized ensemble for predicting reservoir rock properties in petroleum industry by Kenari, Seyed Ali Jafari

    Published 2013
    “…Ensemble is a learning algorithm that combines some experts instead of considering a single best expert for the predictions.The thesis proposed anoptimizing method leading to small structure of assemble GA. …”
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  15. 15
    A modified strength capacity for composite slab using reliability approach

    A modified strength capacity for composite slab using reliability approach by Mohammed, Kachalla

    Published 2016
    “…Similarly, a procedural algorithm lead to the development of pro_led composite slab strength determination function for both longitudinal shear estimation methods by considering section slenderness and deck characteristics. …”
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  16. 16
    Variable block based motion estimation using hexagon diamond full search algorithm (HDFSA) via block subtraction technique

    Variable block based motion estimation using hexagon diamond full search algorithm (HDFSA) via block subtraction technique by Hardev Singh, Jitvinder Dev Singh

    Published 2015
    “…The fixed block matching uses the same block size throughout the motion estimation process while the variable block matching uses different block size. …”
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  17. 17
    Development of an artificial neural network algorithm for predicting the cutting force in end milling of Inconel 718 alloy

    Development of an artificial neural network algorithm for predicting the cutting force in end milling of Inconel 718 alloy by Hossain, Ishtiaq, Amin, A. K. M. Nurul, Patwari, Muhammed Anayet Ullah

    Published 2011
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  18. 18
    Wavelet based fault tolerant control of induction motor / Khalaf Salloum Gaeid

    Wavelet based fault tolerant control of induction motor / Khalaf Salloum Gaeid by Gaeid, Khalaf Salloum

    Published 2012
    “…IMs are an important part of the industry as they provide convenience through their simple construction and a minimum maintenance. In addition they are highly rigid and reliable. …”
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  19. 19
    Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data

    Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data by Baba, Ishaq Abdullahi

    Published 2022
    “…The reweighted fast, consistent and high breakdown (RFCH) estimator is a multivariate procedure used to estimate the robust location and scatter matrix. …”
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  20. 20
    A comparative study on aviation arrival delay prediction using machine learning methods

    A comparative study on aviation arrival delay prediction using machine learning methods by Chew, Pui Ting

    Published 2023
    “…Additionally, the research extends its modelling efforts to assess the viability of constructing a predictive model that can be effectively applied across multiple years and concludes that the 2016 ANN model using four common significant variables from literature review approach and stepwise regression approach can produce F1 scores that exceed 0.81 when used to predict test set data from years 2017 to 2019. …”
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