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  1. 1

    Financial time series predicting using machine learning algorithms by Tiong, Leslie Ching Ow *

    Published 2013
    “…Thereafter, Artificial Neural Network (ANN) and Support Vector Machine (SVM) algorithms are implemented separately to train with the trend patterns for predicting the movement direction of financial trends. …”
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    Thesis
  2. 2

    Development of an intelligent system using Kernel-based learning methods for predicting oil-palm yield. by Md. Sap, Mohd. Noor, Awan, A. Majid

    Published 2005
    “…This paper presents our work on developing an intelligent system for predicting crop yield, for example oil-palm yield, from climate and plantation data. …”
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    Article
  3. 3

    Attitude Control System for InnoSAT by Anon

    Published 2009
    “…The ACS has Adaptive Predictive Fuzzy Logic. The objective of this project is to develop attitude control algorithms that are going to be tested when the InnoSAT is in the orbit. …”
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    Other
  4. 4

    PREDICTING THE PRICE OF COTTON USING RNN AND LSTM by MOHAMAD, AHMAD LUKMAN

    Published 2020
    “…The data will then be separated into training set and testing set and will be feed to the machine learning algorithm to find the pattern and try to do prediction. …”
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    Final Year Project
  5. 5

    Neural Network Controller Implementation on a Supersonic Separator by Mohamad Hanif, Noor Hazrin Hany, Mokhtar, Khairil Anuar

    Published 2009
    “…The controller in use currently implemented a PID algorithm to control the position of the shockwave within the separator. …”
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    Conference or Workshop Item
  6. 6

    Investigation of An Early Prediction System of Cardiac Arrest Using Machine Learning Techniques by Muhammad Afnan, Mohammad Nasir

    Published 2022
    “…To identify approaching heart illness using Machine learning techniques, a preliminary design of a cloud-based heart disease prediction system was developed. An effective machine learning approach created from a separate examination of many machine learning algorithms in WEKA should be applied for the correct identification of heart disease. …”
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    Undergraduates Project Papers
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    SYSTEM IDENTIFICATION AND MODEL PREDICTIVE CONTROL FOR INTERACTING SERIES PROCESS WITH NONLINEAR DYNAMICS by SETYO WIBOWO, TRI CHANDRA

    Published 2009
    “…Several important issues in the identification process and real-time implementation of model predictive control algorithm are also discussed. The proposed method has been successfully demonstrated on a pilot plant and a number of key results obtained in the development process are presented. …”
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    Thesis
  10. 10

    Jaya algorithm hybridized with extreme gradient boosting to predict the corrosion-induced mass loss of agro-waste based monolithic and Ni-reinforced porous alumina by Dele-Afolabi, T.T., Jung, D.W., Ahmadipour, Masoud, Azmah Hanim, M.A., Adeleke, A.O., Kandasamy, M., Gunnasegaran, Prem

    Published 2024
    “…The Jaya-XGBoost model developed in this study effectively predicted the mass loss in NaOH (R2 = 0.9984; MAE = 0.0168) and mass loss in H2SO4 (R2 = 0.9824; MAE = 0.0217) of the monolithic and nickel-reinforced porous alumina. …”
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    Article
  11. 11

    Automatic control of flotation process using computer vision by Saravani, Ali Jahed

    Published 2015
    “…Finally, a control strategy implementing the developed froth model and prediction system was introduced for direct optimization of metallurgical parameters. …”
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    Thesis
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    Real-time and predictive analytics of air quality with IoT system: A review by Nurmadiha, Osman, Mohd Faizal, Jamlos, Fatimah, Dzaharudin, Aidil Redza, Khan, You, Kok Yeow, Khairil Anuar, Khairi

    Published 2020
    “…(iv) Data analytics for Air Pollution Index (API) prediction along with IoT, with various communication protocols can as-sist in the development of real-time, and continuous high precision environmen-tal monitoring systems. v) Machine Learning (ML) Regression algorithm is suit-able for prediction and classification of concentration gas pollutant, while ANN and SVM algorithm is used for forecasting.…”
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    Book Chapter
  14. 14

    A framework for predicting oil-palm yield from climate data by Awan, A. Majid, Md. Sap, Mohd. Noor

    Published 2006
    “…This paper presents work on developing a software system for predicting crop yield, for example oil-palm yield, from climate and plantation data. …”
    Get full text
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    Conference or Workshop Item
  15. 15
  16. 16

    Novel techniques for voltage stability assessment and improvement in power system / Ismail Musirin. by Musirin, Ismail

    Published 2004
    “…Few automatic contingency analysis and ranking algorithms due to line and generator outages were separately developed. …”
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    Thesis
  17. 17

    Jaya algorithm hybridized with extreme gradient boosting to predict the corrosion-induced mass loss of agro-waste based monolithic and Ni-reinforced porous alumina by Dele-Afolabi T.T., Jung D.W., Ahmadipour M., Azmah Hanim M.A., Adeleke A.O., Kandasamy M., Gunnasegaran P.

    Published 2025
    “…The Jaya-XGBoost model developed in this study effectively predicted the mass loss in NaOH (R2 = 0.9984; MAE = 0.0168) and mass loss in H2SO4 (R2 = 0.9824; MAE = 0.0217) of the monolithic and nickel-reinforced porous alumina. …”
    Article
  18. 18

    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

    Published 2018
    “…Three different SAS algorithms (i) bootstrap multiple linear regression (BMLR), (ii) bootstrap weighted Bayesian multiple linear regression (BWBMLR), and (iii) fuzzy bootstrap weighted multiple linear regression (FBWMLR) were compared separately according to their average width of prediction. …”
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    Proceeding Paper
  19. 19

    Identification and Grading of Manage Using Image Processing by Shukor, Syazwan

    Published 2021
    “…Features such as maximum colour component values, pixel area and perimeter are extracted using a feature extraction algorithm for compilation into separate "sv" files for classifier and prediction models training and testing. 3 classes are selected using silhouette analysis in labelling the mango features as training references for classifiers. …”
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    Final Year Project
  20. 20

    A Study on Performance Comparisons between KNN, Random Forest and XGBoost in Prediction of Landslide Susceptibility in Kota Kinabalu, Malaysia by Soo See, Chai, Dorothy, Martin

    Published 2022
    “…Unfortunately, the most accurate algorithm which can be used to develop a landslide susceptibility model is still lacking. …”
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    Proceeding