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  1. 1
    On fractional and semi-soft handover in long term evolution(LTE) networks

    On fractional and semi-soft handover in long term evolution(LTE) networks by Hussein, Yaseein Soubhi, Mohd Ali, Borhanuddin, Varahram, Pooria

    Published 2011
    “…In this paper a hybrid HO algorithms called semi-soft handover (SSHO) and fractional soft handover (FSHO) in long term evolution (LTE) system are studied. …”
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  2. 2
    Liquid slosh suppression by implementing data-driven fractional order pid controller based on marine predators algorithm

    Liquid slosh suppression by implementing data-driven fractional order pid controller based on marine predators algorithm by Mohd Tumari, Mohd Zaidi Mohd, Mustapha, Nik Mohd Zaitul Akmal, Ahmad, Mohd Ashraf, Saat, Shahrizal, Ghazali, Mohd Riduwan

    Published 2023
    “…Thus, this research paper proposed the development of a data-driven fractional-order PID controller based on marine predators algorithm (MPA) for liquid slosh suppression system. …”
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  3. 3
    Liquid slosh suppression by implementing data-driven fractional order PID controller based on marine predators algorithm

    Liquid slosh suppression by implementing data-driven fractional order PID controller based on marine predators algorithm by Mohd Zaidi, Mohd Tumari, Mohd Ashraf, Ahmad, Mohd Riduwan, Ghazali, Nik Mohd Zaitul Akmal, Mustapha, Shahrizal, Saat

    Published 2023
    “…Thus, this research paper proposed the development of a data-driven fractional-order PID controller based on marine predators algorithm (MPA) for liquid slosh suppression system. …”
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  4. 4
    Computational approach via half-sweep and preconditioned aor for fractional diffusion

    Computational approach via half-sweep and preconditioned aor for fractional diffusion by Andang Sunarto, Praveen Agarwal, Jumat Sulaiman, Jackel Vui Lung Chew

    Published 2022
    “…Throughout this paper, a Caputo fractional operator is used to substitute the time-fractional derivative term approximately. …”
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  5. 5
    Operational matrix based on orthogonal polynomials and artificial neural networks methods for solving fractal-fractional differential equations

    Operational matrix based on orthogonal polynomials and artificial neural networks methods for solving fractal-fractional differential equations by Shloof, Aml Melad Asan

    Published 2024
    “…In the second part of the thesis, we developed the Hilfer fractal-fractional derivative definition. …”
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  6. 6
    Hybrid evolutionary-dolphin echolocation programming for sizing optimization of stand-alone photovoltaic systems / Zulkifli Othman

    Hybrid evolutionary-dolphin echolocation programming for sizing optimization of stand-alone photovoltaic systems / Zulkifli Othman by Othman, Zulkifli

    Published 2021
    “…The objectives are 1) to formulate an iterative-based algorithm for sizing optimization of SAPV and (Hybrid Stand-Alone Photovoltaic) HSAPV systems, 2) to develop a hybrid EDEP technique for sizing optimization of SAPV and HSAPV systems and 3) to formulate a hybrid EDEP technique for determining optimal solar fraction in sizing optimization of SAPV and HSAPV system. …”
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  7. 7
    A hybrid technique of deep learning neural networks with finite difference method for higher order fractional Volterra-Fredholm integro-differential equations with φ-Caputo operator

    A hybrid technique of deep learning neural networks with finite difference method for higher order fractional Volterra-Fredholm integro-differential equations with φ-Caputo operato... by Alsa’Di, Kawthar, Nik Long, Nik Mohd Asri

    Published 2025
    “…The numerical examples demonstrated the efficiency of the proposed method in solving the complicated higher order fractional problems of linear and non-linear terms.…”
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  8. 8
    Solar Photovoltaic Maximum Power Point Tracking via Predictive Technique

    Solar Photovoltaic Maximum Power Point Tracking via Predictive Technique by ‘Ainaa Nur Batrisyia binti Abdul Rahman, -

    Published 2022
    “…The first stage of this study is to develop the MPPT algorithm that are commonly divided into six types; Perturb and Observe (P&O), Incremental Conductance (INC), Fractional Open Circuit Voltage (FOVC), Fractional Short Circuit Current (FSCC), Artificial Neural (ANN) and Fuzzy Logic Control (FLC). …”
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  9. 9
    Methodology of rolling horizon scheduling under demand uncertainty

    Methodology of rolling horizon scheduling under demand uncertainty by Romli, Awanis, Ameendeen, Mohamed Ariff, Ahmad, Norasnita

    Published 2006
    “…This model use a combination of an autoregressive fractionally integrated moving average (ARFIMA) forecasting model and fractional differencing method. …”
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  10. 10
    Numerical Analysis of Defects Caused by Thermolysis in an Infinite Cylindrical Ceramic Moulding

    Numerical Analysis of Defects Caused by Thermolysis in an Infinite Cylindrical Ceramic Moulding by Gumel, A. B., Twizell, E. H.

    Published 1999
    “…A parallel algorithm using two processors is developed by taking the partial fraction decomposition of the Pade approximate and a (matrix) rational expression in the recurrence relation.…”
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  11. 11
    Development of integrated models for distribution network design of perishable products

    Development of integrated models for distribution network design of perishable products by Firoozi, Zahra

    Published 2015
    “…A Lagrangian relaxationbased heuristic algorithm is developed to solve the model. The algorithm produces solutions that are within 0.027% of optimality gap.…”
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  12. 12
    The implementation of post-processing data thinning for multibeam echo sounding data

    The implementation of post-processing data thinning for multibeam echo sounding data by Mahmud, Mohd. Razali, Mohd. Yusof, Othman

    Published 2006
    “…Data thinning algorithms should be capable in handling high volume of MBES data. …”
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  13. 13
    Application of artificial neural network to predict brake specific fuel consumption of retrofitted cng engine

    Application of artificial neural network to predict brake specific fuel consumption of retrofitted cng engine by Jahirul, M.I., Saidur, Rahman, Masjuki, Haji Hassan

    Published 2009
    “…Statistical analysis in terms of Root-Mean-Squared (RMS), absolute fraction of variance (R2), as well as mean percentage error is used to investigate the prediction performance of ANN. …”
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  14. 14
    Investigate the Relation between Particle Size Distribution (PSD) Using Image Analysis Method and Chemical Oxygen Demand (COD) In POME Sample

    Investigate the Relation between Particle Size Distribution (PSD) Using Image Analysis Method and Chemical Oxygen Demand (COD) In POME Sample by Mohd Fathilah, Anis Afiqah

    Published 2015
    “…By conducting this research, image analysis algorithm can be developed in monitor the particle size, and the relation between PSD and COD can be observed.…”
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    Final Year Project
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  15. 15
    Investigation of pollutant reduction by simulation of turbulent non-premixed pulverized coal combustion

    Investigation of pollutant reduction by simulation of turbulent non-premixed pulverized coal combustion by Rahmanian, B., Safaei, M.R., Kazi, S.N., Ahmadi, G., Oztop, H.F., Vafai, K.

    Published 2014
    “…A QUICK scheme was adopted for the discretization of all convective terms of the advective transport equations. The static temperature, mass fraction of pollutant NOx, and velocity distribution along the centerline of the burner as well as temperature and NOx contours for different dilution percentages were presented. …”
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  16. 16
    Verification of volume-of-fluid (VOF) simulation for thin liquid film applications

    Verification of volume-of-fluid (VOF) simulation for thin liquid film applications by Balachandran S., Shuaib N.H., Hasini H., Yusoff M.Z.

    Published 2023
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  17. 17
    Analysis of daytime and nighttime ground level ozone concentrations using boosted regression tree technique

    Analysis of daytime and nighttime ground level ozone concentrations using boosted regression tree technique by Yahaya, Noor Zaitun, Ghazali, Nurul Adyani, Ahmad, Sabri, Mohammad Asri, Mohammad Akmal, Ibrahim, Zul Fahdli, Ramli, Nor Azman

    Published 2017
    “…Using the number of trees between 2,500-3,500, learning rate of 0.01, and interaction depth of 5 were found to be the best setting for developing the ozone boosting model. The performance of the O3 boosting models were assessed, and the fraction of predictions within two factor (FAC2), coefficient of determination (R²) and the index of agreement (IOA) of the model developed for day andnighttime are 0.93, 0.69 and 0.73 for daytime and 0.79, 0.55 and 0.69 for nighttime respectively. …”
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  18. 18
    Mathematical modeling of optical and thermal behaviour of a new cascade nanofluid-based PV/T system / Samir Hassani

    Mathematical modeling of optical and thermal behaviour of a new cascade nanofluid-based PV/T system / Samir Hassani by Samir, Hassani

    Published 2017
    “…An improved algorithm for Mie theory was developed to measure nanofluid optical properties. …”
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  19. 19
    Performance investigation and multi-objective optimization of end milling of aluminium alloy 6061 T6 with coated and uncoated carbide tools under various cooling conditions

    Performance investigation and multi-objective optimization of end milling of aluminium alloy 6061 T6 with coated and uncoated carbide tools under various cooling conditions by Syeda Najiha, Masood

    Published 2015
    “…Comprehensive multi-objective optimization model using genetic algorithm is developed to optimize machining performance measures under different MQL conditions, based on Pareto optimal design approach. …”
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  20. 20
    Solubility enhancement of decitabine as anticancer drug via green chemistry solvent: Novel computational prediction and optimization

    Solubility enhancement of decitabine as anticancer drug via green chemistry solvent: Novel computational prediction and optimization by Nader Ibrahim Namazi, Sameer Alshehri, Rawan Bafail, Bader Huwaimel, Amal M. Alsubaiyel, Ali H. Alamri, Ahmed D. Alatawi, Hossam Kotb, Mohd Sani Sarjadi, Md. Lutfor Rahman, Mohammed A.S. Abourehab

    Published 2022
    “…Also, in terms of R-squared score, these models have 0.986, 0.983, and 0.911 scores, respectively. …”
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