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  1. 1
    Fuzzy modeling using Bat Algorithm optimization for classification

    Fuzzy modeling using Bat Algorithm optimization for classification by Noor Amidah, Ahmad Sultan

    Published 2018
    “…A Sazonov Engine which is a fuzzy java engine is use to apply Bat Algorithm in the experiment. …”
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    Undergraduates Project Papers
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  2. 2
    Classification System for Heart Disease Using Bayesian Classifier

    Classification System for Heart Disease Using Bayesian Classifier by Magendram, Anusha

    Published 2007
    “…This system was developing base on to three main part which is data processing, testing and implementation of the algorithm. …”
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    Thesis
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  3. 3
    An ensemble learning method for spam email detection system based on metaheuristic algorithms

    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…Major problems in classification task are large amount of training data, large number of features and different behavior of data streams that reduce accuracy and increase computational cost in classifier training phase. …”
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  4. 4
    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde

    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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  5. 5
    A web-based implementation of k-means algorithms

    A web-based implementation of k-means algorithms by Lee, Quan

    Published 2022
    “…Firstly, k-luster could incorporate additional clustering algorithms, or even classification algorithms in the future. …”
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    Final Year Project / Dissertation / Thesis
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  6. 6
    Face classification for three major ethnic of Orang Asli using Back Propagation Neural Network / Nor Intan Shafini Nasaruddin

    Face classification for three major ethnic of Orang Asli using Back Propagation Neural Network / Nor Intan Shafini Nasaruddin by Nasaruddin, Nor Intan Shafini

    Published 2012
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  7. 7
    Development of fault detection, diagnosis and control system identification using multivariate statistical process control (MSPC)

    Development of fault detection, diagnosis and control system identification using multivariate statistical process control (MSPC) by Ibrahim, Kamarul 'Asri, Ahmad, Arshad, Ali, Mohamad Wijayanuddin, Mak, Weng Yee

    Published 2006
    “…Multivariate Statistical Process Control (MSPC) uses historical data of processes to develop useful process fault detection, diagnosis and control tools. …”
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    Monograph
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  8. 8
    Features selection for intrusion detection system using hybridize PSO-SVM

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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  9. 9
    Formulation of model predictive control algorithm for nonlinear processes

    Formulation of model predictive control algorithm for nonlinear processes by Mohd. Yusof, Khairiyah, Hassim, Mimi Haryani, Tan, Sook Li, Ab. Rashid, Siti Rafidah

    Published 2004
    “…Process control is essential in any chemical plant. …”
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    Monograph
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  10. 10
    Development of Quantification Algorithm for Control Valve Stiction

    Development of Quantification Algorithm for Control Valve Stiction by H., Zabiri, A., Maulud, N., Omar, M. , Ramasamy

    Published 2009
    “…In this paper, Neural-network techniques are investigated in the development of a quantification algorithm for control valve stiction. …”
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    Conference or Workshop Item
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  11. 11
    DC motor control using LQR algorithm

    DC motor control using LQR algorithm by Adezeno, Sagoli Olid

    Published 2008
    “…Hence it is essential for complex algorithm to control real time process system. Programmable Logic Controller (PLC) is known as process models by industries for several years. …”
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  12. 12
    Implementation of generalized predictive control (GPC) for a real-time process control using labview

    Implementation of generalized predictive control (GPC) for a real-time process control using labview by Mohd. Faudzi, Ahmad 'Athif

    Published 2006
    “…Real-time control is an approach to evaluate process system with real-time parameters by controlling selected variables to accomplish the control objectives. …”
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  13. 13
    Neural network based model predictive control for a steel pickling process

    Neural network based model predictive control for a steel pickling process by Kittisupakorn, P., Thitiyasook, P., Hussain, Mohd Azlan, Daosud, W.

    Published 2009
    “…The Levenberg-Marquardt algorithm is used to train the process models. In the control (MPC) algorithm, the feedforward neural network models are used to predict the state variables over a prediction horizon within the model predictive control algorithm for searching the optimal control actions via sequential quadratic programming. …”
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  14. 14
    Real time monitoring and controlling using Petri net algorithm for batch process plant / Mohamad Shaiful Osman

    Real time monitoring and controlling using Petri net algorithm for batch process plant / Mohamad Shaiful Osman by Osman, Mohamad Shaiful

    Published 2010
    “…This thesis searches the basic concepts and uses of the classical method Petri net algorithm in SCADA system to control and monitoring the process plant. …”
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  15. 15
    Controller And Circuitry Design And Implementation For Fire Fighting Robot For MIROC 2014 Competition

    Controller And Circuitry Design And Implementation For Fire Fighting Robot For MIROC 2014 Competition by Reyfill Konnik, Charlie Ivan

    Published 2014
    “…The motor control algorithm is developed by using DC motor control theory, which involves determining the motor's mechanical and electrical parameters.Upon the completion of mechanical fabrication, circuit design and parameter extraction, the process of developing the navigation algorithm begins. …”
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    Final Year Project
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  16. 16
    Computer control of batch process plant (software development)

    Computer control of batch process plant (software development) by Safian, Salehudin

    Published 1995
    “…The optimums PID parameters obtain arc being expected to be implement on the computer control of batch process plant software based on the real-time Proportional, Integral and Derivative (PID) algorithms. …”
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  17. 17
    Development Of Machine Learning User Interface For Pump Diagnostics

    Development Of Machine Learning User Interface For Pump Diagnostics by Lee, Zhao Yang

    Published 2022
    “…Machine Learning is one of the ways as a preventive method by applying the data collected from the clogging experiment in the vibration lab to build up a machine learning model for classification of flow blockage levels in the centrifugal pump. …”
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    Monograph
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  18. 18
    Landslide Susceptibility Mapping with Stacking Ensemble Machine Learning

    Landslide Susceptibility Mapping with Stacking Ensemble Machine Learning by Solihin M.I., Yanto, Hayder G., Maarif H.A.-Q.

    Published 2024
    Conference Paper
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  19. 19
    DESIGN OF CONTROL ALGORITHM FOR pH NEUTRALIZATION

    DESIGN OF CONTROL ALGORITHM FOR pH NEUTRALIZATION by ABDUL HALIM, AQILAH JUANI

    Published 2012
    “…A mathematical model of a specific chemical process is designed as a basis to the development of conventional and advanced controllers. …”
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    Final Year Project
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  20. 20
    Automatic control of flotation process using computer vision

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

    Published 2015
    “…Simulation results indicated the effective performance of the designed control schemes in enhancing theM overall efficiency of the process.…”
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