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

Outlier detection in circular regression model using minimum spanning tree method by Nur Faraidah, Muhammad Di, Siti Zanariah, Satari, Roslinazairimah, Zakaria

“…Therefore, this study aims to develop new algorithms that can detect outliers by using the minimum spanning tree method. …”
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Comparative study of clustering-based outliers detection methods in circular-circular regression model by Siti Zanariah, Satari, Nur Faraidah, Muhammad Di, Yong Zulina, Zubairi, Abdul Ghapor, Hussin

“…This paper is a comparative study of several algorithms for detecting multiple outliers in circular-circular regression model based on the clustering algorithms. …”
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JMASM39: Algorithm for combining robust and bootstrap in multiple linear model regression by Wan Ahmad, Wan Muhamad Amir, Ghazali, Puspa Liza, Mohd Ibrahim, Mohamad Shafiq, Aleng, Azlida, A. Rahim, Hanafi, Abdullah, Zailani

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Comparison between fuzzy bootstrap weighted multiple linear regression and multiple linear regression: a case study for oral cancer modelling by Mohd Ibrahim, Mohamad Shafiq, Wan Ahmad, Wan Muhamad Amir, Hasan, Ruhaya, Harun, Masitah Hayati

“…Methodology: Methodology building is based on the SAS algorithm (SAS 9.4 software) which is a robust computational statistic that consists the combination of robust regression, bootstrap, weighted data, Bayesian, and fuzzy regression method. …”
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Detection of multiple outliners in linear regression using nonparametric methods by Adnan, Robiah

“…Generally, method proposed by Sebert et al. (1998) is based on the use of single linkage clustering algorithm with the Euclidean distances to cluster the points in the plots of standard predicted versus residuals values from a linear regression model. …”
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JMASM algorithms and code algorithm for combining robust and bootstrap in multiple linear model regression (SAS) by Wan Muhamad Amir, Mohamad Shafiq, Hanafi A. Rahim, Puspa Liza Ghazali, Azlida Aleng, Abdullah, Z.

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Statistical modeling via bootstrapping and weighted techniques based on variances by Wan Ahmad, Wan Muhamad Amir, Aleng, Nor Azlida, Ali, Z, Mohd Ibrahim, Mohamad Shafiq

“…This study aims to provide an applied method for multiple logistic regression which is called modified Bayesian logistic regression modeling as an alternative technique for logistic regression analysis that focuses on a combination of the bootstrap method using SAS macro and weighted techniques based on variances using SAS algorithm. …”
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Comparative study of clustering-based outliers detection methods in circular-circular regression model by Siti Zanariah Satari, Nur Faraidah Muhammad Di, Yong Zulina Zubairi, Abdul Ghapor Hussin

“…This paper is a comparative study of several algorithms for detecting multiple outliers in circular-circular regression model based on the clustering algorithms. …”
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Comparative study of clustering-based outliers detection methods in circularcircular regression model by Siti Zanariah, Satari, Nur Faraidah, Muhammad Di, Yong Zulina, Zubairi, Abdul Ghapor, Hussin

“…This paper is a comparative study of several algorithms for detecting multiple outliers in circular-circular regression model based on the clustering algorithms. …”
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Integrated support vector regression and an improved particle swarm optimization-based model for solar radiation prediction by Ghazvinian H., Mousavi S.-F., Karami H., Farzin S., Ehteram M., Hossain M.S., Fai C.M., Hashim H.B., Singh V.P., Ros F.C., Ahmed A.N., Afan H.A., Lai S.H., El-Shafie A.

Pembangunan model regresi poisson sifar-melambung berintegrasi dalam biostatistik by Zafakali, Nur Syabiha

“…The first phase in this research is to refer to the algorithm development procedure to model the Zero-Inflated Poisson Regression method through the bootstrap method and combined with the fuzzy regression method. …”
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Real-Time State of Charge Estimation of Lithium-Ion Batteries Using Optimized Random Forest Regression Algorithm by Hossain Lipu M.S., Hannan M.A., Hussain A., Ansari S., Rahman S.A., Saad M.H.M., Muttaqi K.M.

“…However, proper selection of RFR architecture and hyper-parameters combination remains a key issue to be explored. Hence, a differential search algorithm (DSA) is employed to search for the optimal values of trees and leaves in the RFR algorithm. …”

Enhancing Model Selection Based On Penalized Regression Methods And Empirical Mode Decomposition by Al Jawarneh, Abdullah Suleiman Saleh

“…Moreover, this study tackles the multicollinearity between the decomposition components to enhance the prediction accuracy for creating a fitting model. The proposed techniques are compared with four traditional regression methods employed in the previous study.…”
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Penalized Quantile Regression Methods And Empirical Mode Decomposition For Improving The Accuracy Of The Model Selection by Ambark, Ali Saleh Al-Massri

“…Moreover, selecting the relevant variables when fitting the regression model is critical. Therefore, three methods based on a combination of the empirical mode decomposition (EMD) algorithm and penalized quantile regression have been proposed in this study. …”
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Single-linkage method to detect multiple outliers with different outlier scenarios in circular regression model by Siti Zanariah, Satari, Nur Faraidah, Muhammad Di, Roslinazairimah, Zakaria

“…Then, the clusters are combined into larger clusters, until all the observations are formed in the same cluster. In this study, a single-linkage algorithm method that utilised a circular distance based on the City-block distance as the similarity distance is used. …”
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The potential of a novel support vector machine trained with modified mayfly optimization algorithm for streamflow prediction by Adnan R.M., Kisi O., Mostafa R.R., Ahmed A.N., El-Shafie A.

Robust multivariate least angle regression by Uraibi, Hassan Sami, Midi, Habshah, Rana, Sohel

“…We propose to incorporate the Olive and Hawkins reweighted and fast consistent high breakdown estimator into the robust plug-in LARS method based on correlations. Our proposed method is tested by using a numerical example and a simulation study.…”
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The effect of different distance measures in detecting outliers using clustering-based algorithm for circular regression model by Nur Faraidah, Muhammad Di, Siti Zanariah, Satari

“…It is found that the proposed methods are performed well and applicable for circular regression model.…”
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The Multiple Outliers Detection using Agglomerative Hierarchical Methods in Circular Regression Model by Siti Zanariah, Satari, Nur Faraidah, Muhammad Di, Roslinazairimah, Zakaria

“…In this study, we compared the performance of single-linkage method with another agglomerative hierarchical method, namely average linkage for detecting outlier in circular regression model. …”
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