Search Results - (( simulation optimization mining algorithm ) OR ( variable detection tree algorithm ))

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    Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets by Saeed, Sana

    Published 2019
    “…A new self-adaptive hybrid algorithm (CSCMAES) is introduced for optimization. …”
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    Thesis
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    Logic mining method via hybrid discrete hopfield neural network by Guo, Yueling, Mohd Kasihmuddin, Mohd Shareduwan, Zamri, Nur Ezlin, Li, Jia, Romli, Nurul Atiqah, Mansor, Mohd Asyraf, Ruzai, Wan Nur Aqlili

    Published 2025
    “…To demonstrate the efficacy of the proposed logic mining approach, experiments were conducted using both simulated and real-world datasets. …”
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    Article
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    A novel ensemble decision tree-based CHi-squared Automatic Interaction Detection (CHAID) and multivariate logistic regression models in landslide susceptibility mapping by Althuwaynee, Omar F., Pradhan, Biswajeet, Park, Hyuck Jin, Lee, Jung Hyun

    Published 2014
    “…An ensemble algorithm of data mining decision tree (DT)-based CHi-squared Automatic Interaction Detection (CHAID) is widely used for prediction analysis in variety of applications. …”
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    Article
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    Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari by Satari, Siti Zanariah

    Published 2015
    “…Lastly, we consider the problem of detecting multiple outliers in circular regression models based on the clustering algorithm. …”
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    Thesis
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    Coronary artery stenosis detection and visualization / Tang Sze Ling by Tang, Sze Ling

    Published 2015
    “…The performance evaluation results show that the stenosis detection algorithm performs better average sensitivity than several state-of-the-art algorithms.…”
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    Thesis
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    Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

    Published 2018
    “…To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
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    Thesis
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    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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    Thesis
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    Metaheuristic optimization of perovskite solar cell performance using Taguchi grey relational analysis with grey wolf optimizer by Salehuddin, Fauziyah, Mat Junos @ Yunus, Siti Aisah, Ahmad Jalaludin, Nabilah, Mohd Nazli, Nurul Farina, Arith, Faiz, Mohd Zain, Anis Suhaila, Mohamd Rafidi, Nur Ruzanna, Kaharudin, Khairil Ezwan

    Published 2025
    “…The metaheuristic approach sequentially employs the L27 orthogonal array (OA) Taguchi-based design of experiment (DoE), Grey Relational Analysis (GRA), Multiple Linear Regression (MLR) and Grey Wolf Optimizer (GWO). The L27 OA Taguchi-based DoE is initially employed to mine sufficient output data simulated using one dimensional solar cell capacitance simulator (SCAPS-1D). …”
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    Article
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    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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    Conference or Workshop Item
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    Tree species and aboveground biomass estimation using machine learning, hyperspectral and LiDAR data / Nik Ahmad Faris Nik Effendi by Nik Effendi, Nik Ahmad Faris

    Published 2022
    “…Besides, Artificial Neural Network (ANN) and Random Forest (RF) algorithm was used to predicted the AGB using different combination of variables. …”
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    Thesis
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    Detection of phishing websites using machine learning approaches by Farashazillah Yahya, Magnus Anai, Ryan Isaac W Mahibol, Sidney Allister Frankie, Rio Guntur Utomo, Chong Kim Ying, Eric Ling Nin Wei

    Published 2021
    “…The purpose of the study is to conduct a mini-review of the existing techniques and implement experiments to detect whether a website is malicious or not. The dataset consists of 11,055 observations and 32 variables. …”
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    Proceedings
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    Machine-learning approach using thermal and synthetic aperture radar data for classification of oil palm trees with basal stem rot disease by Che Hashim, Izrahayu

    Published 2021
    “…Infected palms are asymptomatic throughout the disease's early stages, making disease detection challenging. The survival of affected trees must detect BSR at the mild infected (T1) stage. …”
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    Thesis
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    Chemometrics analysis for the detection of dental caries via ultraviolet absorption spectroscopy / Katrul Nadia Basri by Basri, Katrul Nadia

    Published 2023
    “…Dimension reduction algorithm such as LDA and CNN were applied on the spectra to reduce the number of variables to be trained. …”
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    Thesis
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    Random Amplified Polymorphic DNA Analysis of Four Breeds of Sheep in Malaysia by Vijaya Kumar

    Published 1999
    “…Primer OPD-11 detected the highest variance among individuals (91.08%) while primer BRL-02 detected the lowest variance among individuals (8.46%). …”
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    Thesis
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    Gene Selection For Cancer Classification Based On Xgboost Classifier by Teo, Voon Chuan

    Published 2022
    “…XGBoost Classifier is applied in this research, which it is an efficient open-source implementation of the gradient boosted trees algorithm. Gradient boosting is a supervised learning algorithm, which attempts to accurately predict a target variable by combining the estimates of a set of simplifier, weaker models. …”
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    Undergraduates Project Papers