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zainal

PROFESSOR IR. DR. ZAINAL AHMAD P.Eng, MIEM

Qualifications: Dip. (UTM), B.Eng. (Surrey), M.Sc. (Distinction), Ph.D. (Newcastle)
Expertise: Artificial Neural Networks(Multiple Neural Networks), Process Modeling, Model Based Process Control, Neural Network Applications In Chemical Processes

 

    1. Z. Ahmad, N. A. Rahim, Alireza Bahadori & Jie Zhang (2017): Improving Water Quality Index Prediction in Perak River Basin Malaysia through the Combination of Multiple Neural Networks, International Journal of River Basin Management 15 (1) , pp: 79-87, DOI: 10.1080/15715124.2016.1256297IAHR.
    2. Z. Ahmad, N. A. Rahim, Alireza Bahadori & Jie Zhang (2017). AIR POLLUITON INDEX PREDICTION USING MULTIPLE NEURAL NETWORKS, IIUM Journal of Engineering, Accepted in press.
    3. Ahmad Z., Bahadori A., Zhang J., 2017, Prediction of combustion efficiency using multiple neural networks, Chemical Engineering Transactions, 56, 85-90 DOI:10.3303/CET1756015.
    4. Rahim N.A., Ahmad Z., 2017, Graphical user interface application in MatlabTM environment for water and air quality process monitoring, Chemical Engineering Transactions, 56, 97-102 DOI:10.3303/CET1756017.
    5. See Lee Foon, Nazira Anisa Rahim, Ahmad Zainal, Zhang Jie.2017. Selective combination in multiple neural networks predictionsing independent component regression approach, Chemical Engineering Research Bulletin 19: 12-19.
    1. Features selection in modelling using multivariable approach
    2. Reliable Data Based Process Modelling and Monitoring For Process Industry.
    3. Development of soft sensor for monitoring and control
    1. Experimental, Modelling and Control of Lactone Bio-Polymerization Process Using Neural Networks.
    2. Operator Training Simulator Using Plant wide Control for Biodiesel Production from Waste Cooking Oil
    1. Development of Nonlinear Bio-polymerization Process using Neural Networks Model: Case study Bio-polymerization of lactones to polyester.
    2. Development of Neural Controller for MIMO Nonlinear System.
    3. Development of Environmental Quality Predictor Using Feedforward Artificial Neural Network (FANN) in Matlab Graphical User Interface (GUI)