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  1. 1
    Study and Implementation of Data Mining in Urban Gardening

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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  2. 2
    Web-based expert system for material selection of natural fiber- reinforced polymer composites

    Web-based expert system for material selection of natural fiber- reinforced polymer composites by Ahmed Ali, Basheer Ahmed

    Published 2015
    “…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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  3. 3
    Recursive least square and fuzzy modelling using genetic algorithm for process control application

    Recursive least square and fuzzy modelling using genetic algorithm for process control application by Abdul Rahman, Ribhan Zafira, Yusof, Rubiyah, Khalid, Marzuki

    Published 2007
    “…The key issues of finding the best model of the process are described. Results show that fuzzy model with genetic algorithm gives minimum mean squared error compare with recursive least square.…”
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  4. 4
    Optimization of fuzzy model using genetic algorithm for process control application

    Optimization of fuzzy model using genetic algorithm for process control application by Yusof, Rubiyah, Abdul Rahman, Ribhan Zafira, Khalid, Marzuki, Ibrahim, Mohd Faisal

    Published 2011
    “…A technique for the modeling of nonlinear control processes using fuzzy modeling approach based on the Takagi–Sugeno fuzzy model with a combination of genetic algorithm and recursive least square is proposed. …”
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  5. 5
    Widely linear dynamic quaternion valued least mean square algorithm for linear filtering

    Widely linear dynamic quaternion valued least mean square algorithm for linear filtering by Mohammed, Aldulaimi Haydar Imad

    Published 2017
    “…The DQLMS algorithm is extended to the widely linear model forming the WL-DQLMS algorithm in order for the algorithm to be able to capture the full second order statistics. …”
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  6. 6
    Modelling and environmental assessment of heterogeneous catalysis biodiesel process using war algorithm

    Modelling and environmental assessment of heterogeneous catalysis biodiesel process using war algorithm by As Eleyana, Ali

    Published 2013
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    Undergraduates Project Papers
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  7. 7
    Fuzzy modeling using Bat Algorithm optimization for classification

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

    Published 2018
    “…Fuzzy modeling is a process of generating parameters which are fuzzy rule and membership function. …”
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    Undergraduates Project Papers
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  8. 8
    SURE-Autometrics algorithm for model selection in multiple equations

    SURE-Autometrics algorithm for model selection in multiple equations by Norhayati, Yusof

    Published 2016
    “…Meanwhile, practitioners who are usually non-experts and lack of statistical knowledge will face difficulties during the modelling process. Hence, algorithm with a step by step guidance is beneficial in model building, testing and selection. …”
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  9. 9
    M-Factors Fuzzy Time Series for Forecasting Moving Holiday Electricity Load Demand in Malaysia (S/O 14589)

    M-Factors Fuzzy Time Series for Forecasting Moving Holiday Electricity Load Demand in Malaysia (S/O 14589) by Mansor, Rosnalini, Mat Kasim, Maznah, Othman, Mahmod, Zaini, Bahtiar Jamili

    “…The modified algorithm, Weighted Subsethood Segmented Fuzzy Time Series (WeSuSFTS) consists of four main phases; data pre-processing, model development, model implementation and model evaluation. …”
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    Monograph
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  10. 10
    Development of novel algorithm features in the modelling of cyclic processes

    Development of novel algorithm features in the modelling of cyclic processes by Choong, Thomas S.Y., Paterson, William R., Scott, David M.

    Published 2002
    “…We present two novel algorithm features for the transient simulation of cyclic processes that exhibit cyclic steady state (CSS). …”
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  11. 11
    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
    “…To fulfil all these objectives, Model Predictive Control (MPC), an optimal model based control algorithm is definitely the best choice among all the advanced control algorithms available to date. …”
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  12. 12
    Elucidating the effect of process parameters on the production of hydrogen-rich syngas by biomass and coal Co-gasification techniques: A multi-criteria modeling approach

    Elucidating the effect of process parameters on the production of hydrogen-rich syngas by biomass and coal Co-gasification techniques: A multi-criteria modeling approach by Bahadar A., Kanthasamy R., Sait H.H., Zwawi M., Algarni M., Ayodele B.V., Cheng C.K., Wei L.J.

    Published 2023
    “…Biomass; Coal; Complex networks; Errors; Forecasting; Gasification; Hydrogen production; Learning algorithms; Mean square error; Neural networks; Regression analysis; Sensitivity analysis; Support vector machines; Co-gasification; Gaussian process regression; Hydrogen-rich syngas; Machine learning algorithms; Machine-learning; Neural-networks; Process parameters; Regression model; Support vectors machine; Syn gas; Synthesis gas; coal; hydrogen; synfuel; biomass; chemical reaction; detection method; hydrogen; machine learning; multicriteria analysis; algorithm; Article; artificial neural network; biomass; controlled study; gasification; Gaussian processing regression; linear regression analysis; machine learning; mean absolute error; mean square error; parameters; prediction; root mean square error; sensitivity analysis; support vector machine; temperature; Bayes theorem; biomass; Bayes Theorem; Biomass; Coal; Hydrogen; Temperature…”
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  13. 13
    Mapreduce algorithm for weather dataset

    Mapreduce algorithm for weather dataset by Khalid Adam, Ismail Hammad

    Published 2017
    “…Results from the proposed algorithm have been compared with the existing model known as AWK (Alfred Aho, Peter Weinberger, and Brian Kernighan) model. …”
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  14. 14
    Contour generation algorithm for Projection Mask Stereolithography 3D printing process

    Contour generation algorithm for Projection Mask Stereolithography 3D printing process by Faeiz Azizi, Adnan, F. R. M., Romlay

    Published 2018
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  15. 15
    Artificial neural network model for predicting windstorm intensity and the potential damages / Mohd Fatruz Bachok

    Artificial neural network model for predicting windstorm intensity and the potential damages / Mohd Fatruz Bachok by Bachok, Mohd Fatruz

    Published 2019
    “…The other 11 prediction processes which utilised ANN model algorithms (fitting tool), gave R-values for all the algorithms higher than 0.900 except one algorithm equal to 0.8661, meanwhile MSE between 0.22 to 116.41. …”
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  16. 16
    Modelling and optimisation of oil palm trunk core biodelignification using neural network and genetic algorithm

    Modelling and optimisation of oil palm trunk core biodelignification using neural network and genetic algorithm by Abdul Sahli, Fakharudin, Norazwina, Zainol, Zulsyazwan, Ahmad Khushairi

    Published 2019
    “…The 4-10-5-2-1 network architecture had been used to model the process and 10 models were generated randomly. …”
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  17. 17
    Integration of image processing algorithm and deep learning approaches to monitor ginger plant

    Integration of image processing algorithm and deep learning approaches to monitor ginger plant by Tan, Cheng Yong

    Published 2024
    “…This study aims to integrate image processing and deep learning algorithms to monitor the growth of ginger plants. …”
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    Final Year Project / Dissertation / Thesis
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  18. 18
    Algorithmic approaches in model selection of the air passengers flows data

    Algorithmic approaches in model selection of the air passengers flows data by Ismail, Suzilah, Yusof, Norhayati, Tuan Muda, Tuan Zalizam

    Published 2015
    “…Algorithm is an important element in any problem solving situation.In statistical modelling strategy, the algorithm provides a step by step process in model building, model testing, choosing the ‘best’ model and even forecasting using the chosen model.Tacit knowledge has contributed to the existence of a huge variability in manual modelling process especially between expert and non-expert modellers.Many algorithms (automated model selection) have been developed to bridge the gap either through single or multiple equation modelling.This study aims to evaluate the forecasting performances of several selected algorithms on air passengers flow data based on Root Mean Square Error (RMSE) and Geometric Root Mean Square Error (GRMSE).The findings show that multiple models selection performed well in one and two step-ahead forecast but was outperformed by single model in three step-ahead forecasts.…”
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  19. 19
    Optimisation of fed-batch fermentation process using deep reinforcement learning

    Optimisation of fed-batch fermentation process using deep reinforcement learning by Chai, Wan Ying

    Published 2023
    “…The proposed algorithm improves the productivity of yeast while limiting ethanol formation and shows satisfactory performance in dealing with model mismatch and process disturbance.…”
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  20. 20
    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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