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  1. 1
    Optimal operation of a process by integrating dynamic economic optimization and model predictive control formulated with empirical model

    Optimal operation of a process by integrating dynamic economic optimization and model predictive control formulated with empirical model by Tuan, T.T., Tufa, L.D., Mutalib, M.I.A., Ramli, N.M.

    Published 2018
    “…The prediction output of a model is not always asymptotically equal to the measured output of a process. …”
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  2. 2
    Optimal operation of a process by integrating dynamic economic optimization and model predictive control formulated with empirical model

    Optimal operation of a process by integrating dynamic economic optimization and model predictive control formulated with empirical model by Tuan, T.T., Tufa, L.D., Mutalib, M.I.A., Ramli, N.M.

    Published 2018
    “…The prediction output of a model is not always asymptotically equal to the measured output of a process. …”
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  3. 3
    VHDL modeling of IRIS recognition using neural network

    VHDL modeling of IRIS recognition using neural network by Reaz, Mamun Bin Ibne, T., A. Leng, Mohd-Yasin, Faisal, Sulaiman, M. S., Islam, S., Ibrahimy, Muhammad Ibn

    Published 2004
    “…Sigmoid transfer function is used for both hidden layer and output layer neurons. Neuron of each layer is modeled individually using behavioral VHDL. …”
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  4. 4
    Development of a complex network-based integrated multi-layer urban growth and optimisation model for efficient urban traffic network

    Development of a complex network-based integrated multi-layer urban growth and optimisation model for efficient urban traffic network by Rui, Ding

    Published 2018
    “…The complexity and impacts of evolving multi-layer network and the co-evolution model are discussed, to address the multi-layer network and land-use based co-evolution process. …”
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    Thesis
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  5. 5
    Application of simulated neural networks as Non-Linear Modular Modeling Method for predicting shelf life of processed cheese / Sumit Goyal and Gyanendra Kumar Goyal

    Application of simulated neural networks as Non-Linear Modular Modeling Method for predicting shelf life of processed cheese / Sumit Goyal and Gyanendra Kumar Goyal by Goyal, Sumit, Goyal, Gyanendra Kumar

    Published 2012
    “…From this study it is concluded that SNN models are excellent tool for predicting the shelf life of processed cheese.…”
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  6. 6
    Nonlinear Chemical Process Monitoring And Fault Detection Based On Modified Lstm Model

    Nonlinear Chemical Process Monitoring And Fault Detection Based On Modified Lstm Model by Zambri, Muhammad Ridzuan

    Published 2022
    “…The simulation experiment of the Tennessee Eastman (TE) chemical process for modified LSTM model will be using MATLAB software. …”
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    Monograph
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  7. 7
    Rank-based optimal neural network architecture for dissolved oxygen prediction in a 200L bioreactor

    Rank-based optimal neural network architecture for dissolved oxygen prediction in a 200L bioreactor by Mamat, Nor Hana, Mohd Noor, Samsul Bahari, Che Soh, Azura, Taip, Farah Saleena, Ab Rashid, Ahmad Hazri, Jufika Ahmad, Nur Liyana, Mohd Yusuff, Ishak

    Published 2017
    “…Formulation of bioprocess model using process data or data driven technique is able to describe the true process conditions better than a model driven technique that focused on ideal steady state condition of process map the relationship of DO concentration with other physical and chemical process variable that has influence on the process. …”
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  8. 8
    Development of a Neural-Fuzzy Model for Machinability Data Selection in Turning Process

    Development of a Neural-Fuzzy Model for Machinability Data Selection in Turning Process by Kong, Hong Shim

    Published 2008
    “…A neural-fuzzy model has been developed to represent machinability data selection in turning process. …”
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  9. 9
    Modeling of Artificial Diamond Production

    Modeling of Artificial Diamond Production by Aziz, Hisyam Zakwan

    Published 2011
    “…The homogeneity of the nucleation process is not considered as the main purpose it to produce a diamond layer regardless ofhow homogenous the layer is in terms ofnuclei orientation. …”
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    Final Year Project
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  10. 10
    Process fault detection and diagnosis using a dynamic neural networks model

    Process fault detection and diagnosis using a dynamic neural networks model by Abdul Rahman, Ribhan Zafira, Che Soh, Azura, Ahmad, Erny Arniza, Mohd Noor, Samsul Bahari, Gomm, J. B.

    Published 2002
    “…This study describes the application of the multi-layer perceptron (MLP) neural network, trained using back-error propagation, to obtain a representative model of a non-linear process over a wide operational region. …”
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  11. 11
    Application of Artificial Neural Network (ANN) for Modeling of DOC Removal from Antibiotics Aqueous Solution by Fenton Process

    Application of Artificial Neural Network (ANN) for Modeling of DOC Removal from Antibiotics Aqueous Solution by Fenton Process by Elmolla, E. S., Chaudhuri, M.

    Published 2009
    “…The results confirmed that neural network modeling could effectively predict and simulate the behavior of the Fenton process for antibiotics degradation.…”
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  12. 12
    Investigation of the effect of layer thickness and infill material percentage on the performance of low-cost and commercial fused deposition modelling / Muhammad Syamsuzzaman Shamsuddin

    Investigation of the effect of layer thickness and infill material percentage on the performance of low-cost and commercial fused deposition modelling / Muhammad Syamsuzzaman Shams... by Muhammad Syamsuzzaman, Shamsuddin

    Published 2013
    “…Fused deposition modelling (FDM) is one of the common processes in RP. …”
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  13. 13
    Modeling of Thin Layer Drying of Banana (Nendran Spp) under Microwave, Convective and Combined Microwave-Convective Processes

    Modeling of Thin Layer Drying of Banana (Nendran Spp) under Microwave, Convective and Combined Microwave-Convective Processes by G. Pillai, Magesh, I., Regupathi, T., Murugesan

    Published 2011
    “…An appropriate empirical model to represent the drying process was established by analyzing the available literature models with current experimental data. …”
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  14. 14
    Leachate generation rate modeling using artificial intelligence algorithms aided by input optimization method for an MSW landfill

    Leachate generation rate modeling using artificial intelligence algorithms aided by input optimization method for an MSW landfill by Abunama, Taher, Othman, Faridah, Ansari, Mozafar, El-Shafie, Ahmed

    Published 2019
    “…Since minimizing data collection and processing efforts as well as minimizing modeling complexity are critical in the hydrological modeling process, the applied input optimization process and the developed models in this study were able to provide a good performance in the modeling of leachate generation efficiently. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature.…”
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  15. 15
    The Use of Artificial Neural Network (ANN) for Modeling of COD Removal from Antibiotic Aqueous Solution by the Fenton Process

    The Use of Artificial Neural Network (ANN) for Modeling of COD Removal from Antibiotic Aqueous Solution by the Fenton Process by Elmolla, E. S., Chaudhuri, M., Eltoukhy, M. M.

    Published 2010
    “…The results showed that neural network modeling could effectively predict and simulate the behavior of the Fenton process.…”
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    Citation Index Journal
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  16. 16
    Modeling osmotic membrane processes without pressure and porosity simplifications

    Modeling osmotic membrane processes without pressure and porosity simplifications by Chong, Y. K., Liang, Y. Y.

    Published 2025
    “…Most membrane processes favor computational efficiency by utilizing simplified approximation like neglecting the impact of pressure and assuming constant support layer porosity. …”
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  17. 17
    Additive Manufacturing of Copper-ABS Filament by Fused Deposition Modeling (FDM) / N Sa’ude ...[et al.]

    Additive Manufacturing of Copper-ABS Filament by Fused Deposition Modeling (FDM) / N Sa’ude ...[et al.] by Sa’ude, N, Ibrahim, M, Ibrahim, MHI, Wahab, MS, Haq, R, Marwah, OMF, Khirotdin, RK

    Published 2018
    “…The copper-ABS filament was fabricated by single screw extruder machine with different material composition, melting temperature and deposited material on the FDM Machine(Model: Prusa I3) in a layer by a layer processes with appropriate setting on melt temperature and the feed rate. …”
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  18. 18
    Development of a prototype model for fully automated Sarawak layered cake machine

    Development of a prototype model for fully automated Sarawak layered cake machine by Ana Sakura, Zainal Abidin, Annisa, Jamali, W., K. Tan, Andrew Ragai Henry, Rigit, J., S. Chong, M. A., Kiprawi, Johnapi, P. R.

    Published 2014
    “…The automatic machine has includes all basic processes namely filling of mixture to the baking tray, baking, layered, pressing and cooling. …”
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  19. 19
    Mechanical and physical properties of polylactic acid based composite filament using statistical analysis in fused deposition modelling

    Mechanical and physical properties of polylactic acid based composite filament using statistical analysis in fused deposition modelling by Mohamad, Nurul Nadia

    Published 2025
    “…The design of experiment utilised in this study was Taguchi method with three levels of printing process parameter which are layer thickness, printing speed and infill density. …”
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  20. 20
    Influence of clad layer thickness of aluminium alloy by friction surface cladding process

    Influence of clad layer thickness of aluminium alloy by friction surface cladding process by Nor Imrah, Yusoff, L. H., Sulaiman

    Published 2023
    “…Heat is produced during the cladding process by friction at the tool-clad layer and the substrate. …”
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