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  1. 1
    Adaptive persistence layer for synchronous replication (PLSR) in heterogeneous system

    Adaptive persistence layer for synchronous replication (PLSR) in heterogeneous system by Beg, Abul Hashem

    Published 2011
    “…The PLSR architecture model, workflow and algorithms are described. The PLSR has been developed using Java Programming language. …”
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    Thesis
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  2. 2
    Mapreduce algorithm for weather dataset

    Mapreduce algorithm for weather dataset by Khalid Adam, Ismail Hammad

    Published 2017
    “…The well-known method for Big Data analytics is MapReduce Model. Nevertheless, the usage of MapReduce Model in processing weather dataset is not widely explored. …”
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  3. 3
    MapReduce algorithm for weather dataset

    MapReduce algorithm for weather dataset by Majid, Mazlina A., Romli, Awanis, Ahmad, Noraziah, Hammad, Khalid Adam Ismail

    Published 2018
    “…The well-known method for Big Data analytics is MapReduce Model. Nevertheless, the usage of MapReduce Model in processing weather dataset is not widely explored. …”
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    Research Report
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  4. 4
    Fuzzy modeling using Bat Algorithm optimization for classification

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

    Published 2018
    “…In order to create parameters, there are many problems arise in the process of fuzzy modeling. The problems are data incomplete and the size of the data is large. …”
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    Undergraduates Project Papers
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  5. 5
    Workflow optimization in distributed computing environment for stream-based data processing model / Saima Gulzar Ahmad

    Workflow optimization in distributed computing environment for stream-based data processing model / Saima Gulzar Ahmad by Saima Gulzar, Ahmad

    Published 2017
    “…To avoid such overheads many techniques have been used, however in this thesis stream-based data processing model is used in which data is processed in the form of continuous instances of data items. …”
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  6. 6
    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
    “…In this thesis, a new quaternion gradient based adaptive algorithm for FIR adaptive filter is developed. The proposed algorithm is capable of processing the generality of quaternion and complex data signals in both noisy and noise-free environments. …”
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  7. 7
    SURE-Autometrics algorithm for model selection in multiple equations

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

    Published 2016
    “…The SURE-Autometrics is also validated using two sets of real data by comparing the forecast error measures with five model selection algorithms and three non-algorithm procedures. …”
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  8. 8
    SUDOKU HELPER

    SUDOKU HELPER by Abdul Razak, Muhammad Asyraf

    Published 2015
    “…In this paper research, author presents an algorithm to provide a tutorial for any Sudoku player who got stuck during the solving process. …”
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    Final Year Project
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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
    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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    Conference or Workshop Item
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  11. 11
    The development of an algorithm and a model through image processing and remote sensing techniques for assessing environmental impacts of routine carbon footprint in Peninsular Malaysia.

    The development of an algorithm and a model through image processing and remote sensing techniques for assessing environmental impacts of routine carbon footprint in Peninsular Mal... by Mat Jafri, Mohd. Zubir

    Published 2015
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  12. 12
    Development of decentralized data fusion algorithm with optimized kalman filter.

    Development of decentralized data fusion algorithm with optimized kalman filter. by Quadri, Sayed Abulhasan

    Published 2016
    “…The model collaborates data fusion technology with algorithm engineering domain, accordingly data fusion algorithm is optimized using sophisticated technique such as functional programming to reduce the processing delay and memory usage. …”
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  13. 13
    Weighted subsethood and reasoning based fuzzy time series for moving holiday electricity load demand forecasting

    Weighted subsethood and reasoning based fuzzy time series for moving holiday electricity load demand forecasting by Rosnalini, Mansor

    Published 2021
    “…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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  14. 14
    Supervised deep learning algorithms for process fault detection and diagnosis under different temporal subsequence length of process data

    Supervised deep learning algorithms for process fault detection and diagnosis under different temporal subsequence length of process data by Terence Chia Yi Kai, Agus Saptoro, Zulfan Adi Putra, King Hann Lim, Wan Sieng Yeo, Jaka Sunarso

    Published 2025
    “…Industrial process time series data could be processed with ease by deep learning algorithms, particularly transformer-based models because of their multi-head attention mechanism. …”
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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
    “…This development corresponds to the windstorm hazard monitoring mechanism which is not available in the country. The predictive model includes 16 prediction processes with 20 back-propagation algorithms whereby radar imageries and meteorological station data were used as a raw data input. …”
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  16. 16
    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
    “…Several machine learning models and related algorithms were developed for prediction of total cases and total deaths. …”
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  17. 17
    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
    “…Several machine learning models and related algorithms were developed for prediction of total cases and total deaths. …”
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  18. 18
    Monthly rainfall prediction model of Peninsular Malaysia using clonal selection algorithm

    Monthly rainfall prediction model of Peninsular Malaysia using clonal selection algorithm by Rodi, N.S.Noor, Malek, M.A, Ismail, Amelia Ritahani

    Published 2018
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  19. 19
    An improved scatter search algorithm for parameter estimation in large-scale kinetic models of biochemical systems

    An improved scatter search algorithm for parameter estimation in large-scale kinetic models of biochemical systems by Remli, Muhammad Akmal, Mohamad, Mohd Saberi, Deris, Safaai, Sinnott, Richard, Napis, Suhaimi

    Published 2019
    “…However, one of the primary challenges in model building is parameter estimation. It is the process to find nearoptimal values of kinetic parameters which may culminate in the best fit of model prediction to experimental data. …”
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  20. 20
    An Improved Scatter Search Algorithm for Parameter Estimation in Large-Scale Kinetic Models of Biochemical Systems

    An Improved Scatter Search Algorithm for Parameter Estimation in Large-Scale Kinetic Models of Biochemical Systems by Muhammad Akmal, Remli, Mohd Saberi, Mohamad, Safaai, Deris, Sinnott, Richard O., Suhaimi, Napis

    Published 2019
    “…However, one of the primary challenges in model building is parameter estimation. It is the process to find nearoptimal values of kinetic parameters which may culminate in the best fit of model prediction to experimental data. …”
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