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  1. 1

    Improved Boosting Algorithms by Pre-Pruning and Associative Rule Mining on Decision Trees for predicting Obstructive Sleep Apnea by Doreen Ying Ying, Sim, Chee Siong, Teh, Ahmad Izuanuddin, Ismail

    Published 2017
    “…An improved Boosting algorithm, named as Boosted PARM-DT, was developed by pre-pruning techniques and Associative Rule Mining (ARM) on decision trees built from the clinical datasets** collected for Obstructive Sleep Apnea (OSA). …”
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    Article
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    An Automated System For Classifying Conference Papers by Ngan, Seon Choon Han

    Published 2021
    “…A randomised stratified 5- fold cross validation was then applied on several data mining algorithms and evaluated using the F-measure as a metric. …”
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    Final Year Project / Dissertation / Thesis
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    Prediction Of Leaf Mechanical Properties Based On Geometry Features With Data Mining by H’ng, Choo Wooi

    Published 2019
    “…The linear models and rules developed from the M5P algorithm were adopted for the FT indicator prediction modelling of 14 attributes. …”
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    Thesis
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    Predicting heart disease using ant colony optimization / Siti Aisyah Ismail by Ismail, Siti Aisyah

    Published 2021
    “…Thus, this study used the Ant Colony Optimization algorithm with data mining called Ant-Miner to predict heart disease because it is said that Ant-Miner’s rule list is simpler than other rule induction algorithms. …”
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    Student Project
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    Application of Optimization Methods for Solving Clustering and Classification Problems by Shabanzadeh, Parvaneh

    Published 2011
    “…Cluster and classification analysis are very interesting data mining topics that can be applied in many fields. …”
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    Thesis
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    Ranking-based pruning and weighted support model for gene association in frequent itemsets / Sofianita Mutalib by Mutalib, Sofianita

    Published 2019
    “…Biological domain is one of the critical areas that always seek for useful knowledge and patterns observed through available methods, including data mining. …”
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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
    “…In the developed feature selection approach, multi-objective binary-valued backtracking search algorithm (MOBBSA) is used as an efficient evolutionary search algorithm to search within different combinations of input variables and selects the non-dominated feature subsets, which minimize simultaneously both the estimation error and the number of features. …”
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    Thesis
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    Portfolio optimization with percentage error-based fuzzy random data for industrial production by Othman, Mohammad Haris Haikal, Arbaiy, Nureize, Che Lah, Muhammad Shukri, Pei, Chun Lin

    Published 2024
    “…The efficacy of this approach is demonstrated in agricultural planning, evaluating five distinct industrial production types: Agriculture, Mining, Manufacturing, Electricity, and Water. The findings underscore the effectiveness of the proposed methodology in managing uncertainties, reducing errors in model development stages, and providing a robust framework for optimal portfolio selection tailored to industrial production contexts, thereby enhancing decision-making processes in uncertain environments…”
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    Conference or Workshop Item
  17. 17

    Portfolio optimization with percentage error-based fuzzy random data for industrial production by Othman, Mohammad Haris Haikal, Arbaiy, Nureize, Che Lah, Muhammad Shukri, Lin, Pei-Chun

    Published 2024
    “…The efficacy of this approach is demonstrated in agricultural planning, evaluating five distinct industrial production types: Agriculture, Mining, Manufacturing, Electricity, and Water. The findings underscore the effectiveness of the proposed methodology in managing uncertainties, reducing errors in model development stages, and providing a robust framework for optimal portfolio selection tailored to industrial production contexts, thereby enhancing decision-making processes in uncertain environments.…”
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    Conference or Workshop Item
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    Modeling of CO emissions from traffic vehicles using artificial neural networks by Al-Gbur, Omer Saud Azeez, Pradhan, Biswajeet, Mohd Shafri, Helmi Zulhaidi, Shukla, Nagesh, Lee, Chang Wook, Rizeei, Hossein Mojaddadi

    Published 2019
    “…The hybrid model was developed based on the integration of GIS and the optimized Artificial Neural Network algorithm that combined with the Correlation based Feature Selection (CFS) algorithm to predict the daily vehicular CO emissions and generate prediction maps at a microscale level in a small urban area by using a field survey and open source data, which are the main contributions to this paper. …”
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    Article
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    Small Dataset Learning In Prediction Model Using Box-Whisker Data Transformation by Lateh, Masitah bdul

    Published 2020
    “…These gaps should be filled with observations in a complete dataset. However, these observations are not available. …”
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    Thesis
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    Simultaneous measurement of multiple soil properties through proximal sensor data fusion: a case study by Wenjun, Ji, Adamchuk, Viacheslav I., Song, Chao Chen, Mat Su, Ahmad S., Ismail, Ashraf, Qianjun, Gan, Zhou, Shi, Biswas, Asim

    Published 2019
    “…After choosing the optimal sensor combination for each soil property, the predictive capability was compared using different data mining algorithms, including support vector machines (SVM), random forest (RF), multivariate adaptive regression splines (MARS), and regression trees (CART). …”
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    Article