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  1. 1
    Model structure selection for a discrete-time non-linear system using a genetic algorithm

    Model structure selection for a discrete-time non-linear system using a genetic algorithm by Ahmad, R., Jamaluddin, H., Hussain, M. A.

    Published 2004
    “…They offer many advantages such as global search characteristics, and this has led to the idea of using this programming method in modelling dynamic non-linear systems. In this paper, a methodology for model structure selection based on a genetic algorithm was developed and applied to non-linear discrete-time dynamic systems. …”
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  2. 2
    Model structure selection for a discrete-time non-linear system using a genetic algorithm

    Model structure selection for a discrete-time non-linear system using a genetic algorithm by Ahmad, R., Jamaluddin, H., Hussain, M. A.

    Published 2004
    “…They offer many advantages such as global search characteristics, and this has led to the idea of using this programming method in modelling dynamic non-linear systems. In this paper, a methodology for model structure selection based on a genetic algorithm was developed and applied to non-linear discrete-time dynamic systems. …”
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  3. 3
    Model structure selection for a discrete-time non-linear system using genetic algorithm

    Model structure selection for a discrete-time non-linear system using genetic algorithm by Ahmad, Robiah, Jamaluddin , Hishamuddin, Hussain, Mohd. Azlan

    Published 2004
    “…They offer many advantages such as global search characteristics, and this has led to the idea of using this programming method in modelling dynamic non-linear systems. In this paper, a methodology for model structure selection based on a genetic algorithm was developed and applied to non-linear discrete-time dynamic systems. …”
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  4. 4
    Model structure selection for a discrete-time non-linear system using a genetic algorithm

    Model structure selection for a discrete-time non-linear system using a genetic algorithm by Ahmad, R., Jamaluddin, H., Hussain, Mohd Azlan

    Published 2004
    “…They offer many advantages such as global search characteristics, and this has led to the idea of using this programming method in modelling dynamic non-linear systems. In this paper, a methodology for model structure selection based on a genetic algorithm was developed and applied to non-linear discrete-time dynamic systems. …”
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  5. 5
    Identification of continuous-time hammerstein system using sine cosine algorithm

    Identification of continuous-time hammerstein system using sine cosine algorithm by E. F., Junis, J. J., Jui, Mohd Helmi, Suid, Mohd Ashraf, Ahmad

    Published 2019
    “…This paper presents the development of identification of continuous-time Hammerstein systems based on Sine Cosine Algorithm (SCA). …”
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    Conference or Workshop Item
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  6. 6
    Real time nonlinear filtered-x lms algorithm for active noise control

    Real time nonlinear filtered-x lms algorithm for active noise control by Sahib, Mouayad Abdulredha

    Published 2012
    “…The developed THF-NLFXLMS algorithm is tested by means of simulation and implemented experimentally using FPGA-based real time controller for a nonlinear ANC application. …”
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    Thesis
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  7. 7
    Development of optimization Alghorithm for uncertain non-linear dynamical system

    Development of optimization Alghorithm for uncertain non-linear dynamical system by Abdul Aziz, Mohd. Ismail, Yaacob, Nazeeruddin, Mohd. Said, Norfarizan, Hamzah, Nor Hazadura

    Published 2004
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    Monograph
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  8. 8
    Performance comparison of different machine learning algorithms on a time-series of covid-19 data: A case study for Saudi Arabia

    Performance comparison of different machine learning algorithms on a time-series of covid-19 data: A case study for Saudi Arabia by Ahmad, M.T., Qaiyum, S., Alamri, A., Islam, S.

    Published 2021
    “…Prediction of total cases and total deaths are obtained by taking previous 14 days of time series data as the input to the machine learning algorithms developed in this paper. …”
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  9. 9
    Performance comparison of different machine learning algorithms on a time-series of covid-19 data: A case study for Saudi Arabia

    Performance comparison of different machine learning algorithms on a time-series of covid-19 data: A case study for Saudi Arabia by Ahmad, M.T., Qaiyum, S., Alamri, A., Islam, S.

    Published 2021
    “…Prediction of total cases and total deaths are obtained by taking previous 14 days of time series data as the input to the machine learning algorithms developed in this paper. …”
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  10. 10
    Use of a non-linear algorithm to improve the maximum length sequence auditory brainstem response

    Use of a non-linear algorithm to improve the maximum length sequence auditory brainstem response by Nik Mohamad, Nik Amnah, Dzulkarnain, Ahmad Aidil Arafat, Wilson, Wayne, Bradley, A. P., Petoe, Matthew, Smith, Andrew, Jamaluddin, Saiful Adli, Rahmat, Sarah, Moon, Jackie

    Published 2012
    “…The present study has developed a new non linear MLS (nlMLS) which aims to overcome the mismatch between the non-linearity of the auditory system and the linearity aspect of the algorithm. …”
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    Proceeding Paper
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  11. 11
    Sustainable Management Of River Water Quality Using Artificial Intelligence Optimisation Algorithms

    Sustainable Management Of River Water Quality Using Artificial Intelligence Optimisation Algorithms by Chia, See Leng

    Published 2021
    “…Least Square Support Vector Machine (LSSVM) base models with linear kernel, polynomial kernel and Radial Basis Function (RBF) kernel and its hybrid models with integration of Hybrid of Particle Swarm Optimisation and Genetic Algorithm (HPSOGA), Whale Optimisation Algorithm based on Self-adapting Parameter Adjustment and Mix Mutation Strategy (SMWOA) and Ameliorative Moth Flame Optimisation (AMFO) were developed and used to predict the WQI at stations 1K06, 1K07 and 1K08 of the Klang River in Selangor, Malaysia. …”
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    Final Year Project / Dissertation / Thesis
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  12. 12
    A mixed integer linear programming model for real-time task scheduling in multiprocessor computer system

    A mixed integer linear programming model for real-time task scheduling in multiprocessor computer system by Oluwadare, Samuel Adeboyo, Akinnuli, Basil Oluwafemi

    Published 2012
    “…The advent of multi-processor systems offers a more efficient way of processing multimedia data in real-time.With the development of appropriate scheduling algorithm, another challenge is the mode of assigning tasks in multi-processor systems.This calls for the use of an appropriate mathematical model that will take cognizance of the nature of variables involved.In this research work, a Mixed Integer Linear Programming Model (MILP) was developed to assign tasks in a multiprocessor system.The MILP model was used to assign tasks to multi-processor systems ranging between 5 and 10 homogeneous processors.The result of the simulation runs shows that with the appropriate scheduling algorithm, a high success rate ratio and guaranteed number of deadlines met could be achieved.…”
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  13. 13
    Simplified adaptive linear neuron harmonics extraction algorithm for dynamic performance of shunt active power filter

    Simplified adaptive linear neuron harmonics extraction algorithm for dynamic performance of shunt active power filter by Mohd Zainuri, Muhammad Ammirrul Atiqi, Mohd Radzi, Mohd Amran, Che Soh, Azura, Mariun, Norman, Abd Rahim, Nasrudin

    Published 2016
    “…This paper presents a single-phase shunt active power filter with artificial intelligence based algorithms by introducing a new Simplified Adaptive Linear Neuron (ADALINE) algorithm for harmonics extraction. …”
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  14. 14
    Linear-pso with binary search algorithm for DNA motif discovery / Hazaruddin Harun

    Linear-pso with binary search algorithm for DNA motif discovery / Hazaruddin Harun by Harun, Hazaruddin

    Published 2015
    “…However due to the longer time required for complete execution of this algorithm, the Binary Search technique was integrated and a new version of the algorithm was developed, namely the Linear-PSO with Binary Search (LPBS) algorithm. …”
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  15. 15
    Use of a non-linear algorithm to improve the maximum length sequence auditory brainstem response

    Use of a non-linear algorithm to improve the maximum length sequence auditory brainstem response by Dzulkarnain, Ahmad Aidil Arafat, Wilson, Wayne, Bradley, Andrew, Nik Mohamad, Nik Amnah, Petoe, Matthew, Smith, Andrew, Jamaluddin, Saiful Adli, Ali Hanafiah, Nurlin

    Published 2012
    “…The present study has developed a new non linear MLS (nlMLS) which aims to overcome the mismatch between the non-linearity of the auditory system and the linearity aspect of the algorithm. …”
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    Proceeding Paper
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  16. 16
    Fusion of linear and nonlinear functional model for cadastral network adjustment / Nazurah Syahzanani Amiruddin

    Fusion of linear and nonlinear functional model for cadastral network adjustment / Nazurah Syahzanani Amiruddin by Amiruddin, Nazurah Syahzanani

    Published 2024
    “…Due to the significant discrepancy in functional models, this study begins with the identification of an algorithm to harmonize the linear (GNSS vectors) and non-linear (traverse) models. …”
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    Student Project
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  17. 17
    The implications for ahybrid detection technique against malicious sqlattacks on web applications

    The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

    Published 2025
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  18. 18
    Enhancing electricity consumption forecasting in limited dataset: A simple stacked ensemble approach incorporating simple linear and support vector regression for Malaysia

    Enhancing electricity consumption forecasting in limited dataset: A simple stacked ensemble approach incorporating simple linear and support vector regression for Malaysia by Chuan, Zun Liang, Shao Jie, Ong, Yim Hin, Tham, Siti Nur Syamimi, Mat Zain, Yunalis Amani, Abdul Rashid, Ainur Naseiha, Kamarudin

    Published 2025
    “…Analysis revealed that this simple stacked ensemble SVR-based time-series algorithm, employing an ε -insensitive loss function with a third-degree polynomial kernel, outperformed 71 other SVR-based algorithms, including four time-series algorithms from the previous study. …”
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  19. 19
    Recent research in cooperative path planning algorithms for multi-agent using mixed- integer linear programming

    Recent research in cooperative path planning algorithms for multi-agent using mixed- integer linear programming by Che Ku, Nor Azie Hailma, Omar, Rosli, Sabudin Elia Nadira, Sabudin Elia Nadira

    Published 2016
    “…Path planning is one of the issues to be handled in the development of autonomous systems. For a group of agents, cooperative path planning is crucial to ensure that a given mission is accomplished in the shortest time possible with optimal solution. …”
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  20. 20
    Photovoltaic shunt active power filter based on indirect self-charging with step size error cancellation and simplified adaptive linear neuron

    Photovoltaic shunt active power filter based on indirect self-charging with step size error cancellation and simplified adaptive linear neuron by Mohd Zainuri, Muhammad Ammirrul Atiqi

    Published 2017
    “…Laboratory prototype was then developed and digital signal processor (DSP) TMS320F28335 was used to perform the computation of algorithms. …”
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