Search Results - (( parameter relationship tree algorithm ) OR ( java adaptation optimization algorithm ))

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    Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor by Adilah, Abdul Ghapor

    Published 2017
    “…This research focuses on the parameter estimation, outlier detection and imputation of missing values in a linear functional relationship model (LFRM). …”
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    Thesis
  3. 3

    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

    Phylogenetic relationships of Malaysian monkeys, Cercopithecidae, based on mitochondrial cytochrome c sequences by Md-Zain, B.M., Mohamad, M., Ernie-Muneerah, M.A., Ampeng, A., Jasmi, A., Lakim, M., Mahani, M.C.

    Published 2010
    “…In addition, tree topologies indicate a good resolution of the Colobinae phylogenetic relationships at the intergeneric level, but with low bootstrap support. …”
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    Article
  5. 5

    Determination of tree stem volume : A case study of Cinnamomum by Noraini Abdullah

    Published 2013
    “…Modelling of trees has attracted scientific research in various fields and disciplines since trees and forests play very important roles in the global system. …”
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  6. 6

    Application of machine learning algorithms to predict removal efficiency in treating produced water via gas hydrate-based desalination by Nallakukkala, Sirisha, Tackie-Otoo, Bennet Nii, Aliyu, Ruwaida, Lal, Bhajan, Nallakukkala, Jagadish Ram Deepak, Devi, Gayathri

    Published 2025
    “…In this context. ML algorithms provide powerful data driven means to model complex relationship within experimental datasets to improve process optimisation This study systematically evaluated several supervised ML models, including Random Forest (RF) Support Vector Machines (SVM), Ridge Regression, Lasso Regression, Decision Tree, Extra Tree Regression, Gradient Boost, and XGBoost, to predict removal efficiency in GHBD system. …”
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  7. 7

    Prospects for basal stem rot disease based on soil apparent electrical conductivity in oil palm plantation by Mohd Husin, Ezrin

    Published 2020
    “…Interpolation techniques were done for all data by using ArcMap to identify the soil variability. The relationship of soil parameters, soil ECa, and soil nutrient contents was analysed using the statistical method in the SPSS software package. …”
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  8. 8

    Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions by Saraswati, Galuh Wilujeng

    Published 2017
    “…The project has also implemented the optimization process onto the proposed ANFIS model through the hybrid of Genetic Algorithm on the fuzzy membership function of the ANFIS model. …”
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  9. 9

    Landslide susceptibility mapping using decision-tree based chi-squared automatic interaction detection (CHAID) and logistic regression (LR) integration by Althuwaynee, Omar F., Pradhan, Biswajeet, Ahmad, Noordin

    Published 2014
    “…This study proved the efficiency and reliability of decision tree (DT) model in landslide susceptibility mapping. …”
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  10. 10

    Machine learning models for predicting the compressive strength of concrete with shredded pet bottles and m sand as fine aggregate by Nadimalla, Altamashuddinkhan, Masjuki, Siti Aliyyah, Gubbi, Abdullah, Khan, Anjum, Mokashi, Imran

    Published 2025
    “…Conversely, the Artificial Neural Network (ANN) model exhibited the least accuracy, with the highest errors (MSE of 112.33 and MAE of 8.52) and a negative R² score (-0.64), indicating poor model training and an inability to capture the relationships between parameters effectively, partly due to the relatively small dataset. …”
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  11. 11

    Price prediction model of green building based on machine learning algorithms / Nur Syafiqah Jamil by Jamil, Nur Syafiqah

    Published 2021
    “…The experiment involved five (5) common algorithms: Linear Regressor, Decision Tree Regressor, Random Forest Regressor, Ridge Regressor and Lasso Regressor. …”
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    Thesis
  12. 12

    State of charge estimation for electric vehicles using random forest by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

    Published 2024
    “…By leveraging decision trees and ensemble learning, the RF model forms resilient relationships between input parameters, such as voltage, current, ambient temperature, and battery temperatures, and SOC values. …”
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    Article