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Comparison between fuzzy bootstrap weighted multiple linear regression and multiple linear regression: a case study for oral cancer modelling
Published 2018“…(MLR) is the most common type of linear regression analysis. Current technology advancement and increasing of development of the new or modified methodology building leads to the development of an alternative method for multiple linear regression model calculation. …”
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Outlier detection in circular regression model using minimum spanning tree method
Published 2019“…Therefore, this study aims to develop new algorithms that can detect outliers by using the minimum spanning tree method. …”
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Conference or Workshop Item -
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Performance comparison of different machine learning algorithms on a time-series of covid-19 data: A case study for Saudi Arabia
Published 2021“…Several machine learning models and related algorithms were developed for prediction of total cases and total deaths. …”
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Performance comparison of different machine learning algorithms on a time-series of covid-19 data: A case study for Saudi Arabia
Published 2021“…Several machine learning models and related algorithms were developed for prediction of total cases and total deaths. …”
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Pembangunan model regresi poisson sifar-melambung berintegrasi dalam biostatistik
Published 2018“…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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Thesis -
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Predictive models for hotspots occurrence using decision tree algorithms and logistic regression.
Published 2013“…Furthermore, the logistic regression model outperforms the decision tree algorithms with the accuracy of 68.63%. …”
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Predicting sea levels using ML algorithms in selected locations along coastal Malaysia
Published 2025“…Data compiled from 1985 to 2018 was utilized for training and testing the developed models. An assessment of the multiple statistics-driven regression algorithms resulted such that each tested location was associated with a particular preferred model. …”
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Modeling and prediction of the specific heat capacity of Al₂O₃/water nanofluids using hybrid genetic algorithm/support vector regression model
Published 2019“…The proposed (genetic algorithm/support vector regression) GA/SVR model was formulated using volume fractions and specific heat capacities of the alumina nanoparticles. …”
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Investigating the Application of Artificial Intelligence for Earthquake Prediction in Terengganu
Published 2023text::Thesis -
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Diamond price prediction using random forest algorithm / Nur Amirah Mohd Azmi
Published 2025“…Development for a customized Random Forest-based model and a library-based one is performed. …”
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Predicting sea levels using ML algorithms in selected locations along coastal Malaysia
Published 2024“…Data compiled from 1985 to 2018 was utilized for training and testing the developed models. An assessment of the multiple statistics-driven regression algorithms resulted such that each tested location was associated with a particular preferred model. …”
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Estimating the refractive index of oxygenated and deoxygenated hemoglobin using genetic algorithm – support vector regression model
Published 2018“…Methods: These models utilized experimental data of wavelengths and hemoglobin concentrations in building highly accurate Genetic Algorithm/Support Vector Regression model (GA-SVR).Results:The developed methodology showed high accuracy as indicated by the low root mean square error values of 4.65 × 10−4 and 4.62 × 10−4 for oxygenated and deoxygenated hemoglobin, respectively. …”
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Sales prediction for media platforms advertising expenditure using Linear Regression / Nur Athirah Abdurahman
Published 2023“…The methodology employed in this project involves the implementation of the Linear Regression algorithm, a statistical modeling technique that analyzes the relationship between advertising expenditure and sales. …”
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Thesis -
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Energy band gap modeling of doped bismuth ferrite multifunctional material using gravitational search algorithm optimized support vector regression
Published 2021“…The energy band gap of doped bismuth ferrite is modeled in this contribution through the fusion of a support vector regression (SVR) algorithm with a gravitational search algorithm (GSA) using crystal lattice distortion as a predictor. …”
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