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  1. 1
    Backstepping Integral Super Twisting Sliding Mode Control Algorithm For Autonomous Underwater Glider

    Backstepping Integral Super Twisting Sliding Mode Control Algorithm For Autonomous Underwater Glider by Noh, Maziyah Mat

    Published 2019
    “…The BISTSMC was tested for external disturbance and parameter variations. The BISTSMC has been benchmarked its performances with other sliding mode control (SMC) strategies to evaluate the chattering suppression of the controllers. …”
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  2. 2
    The effect of key parameters on the design of an optimized CAES power plant

    The effect of key parameters on the design of an optimized CAES power plant by Khalaji Assadi , M, Shamshirgaran , S.R, Defaee Rad, S

    Published 2017
    “…In order to obtain a more tangible realization, it is necessary to verify the results against the variation of key parameters. In this study, the sensitivity analysis is performed based on main parameters including plant loading and ambient condition and the resultant trends of each case are presented. …”
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  3. 3
    Development and Application of a Finite Element Distributed Rainfall Runoff Simulation Model

    Development and Application of a Finite Element Distributed Rainfall Runoff Simulation Model by Huang, Yuk Feng

    Published 2000
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  4. 4
    Development of controller for an underactuated autonomous underwater vehicle (AUV)

    Development of controller for an underactuated autonomous underwater vehicle (AUV) by Mat-Noh, Maziyah, Zain, Zainah Md, Abd Ghani, N. M., Abdul Wahab, Yasmin, Razali, Akhtar Razul

    Published 2019
    “…The simulation results have shown that the proposed controller provides the smallest chattering about more than 1000 times smaller than STSMC, more than 100 times smaller than back-stepping SMC in nominal, disturbance and parameter variation cases respectively. The steady error of the proposed controller also gives the smallest steady state error of four times smaller than STSMC and back-stepping SMC in all cases for pitching angle and 100 times smaller than STSMC and back-stepping for excess mass. …”
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  5. 5
    Scheduling dynamic cellular manufacturing systems in the presence of cost uncertainty using heuristic method

    Scheduling dynamic cellular manufacturing systems in the presence of cost uncertainty using heuristic method by Delgoshaei, Aidin

    Published 2016
    “…It is observed that in 67% of studied cases, inflation rate can strengthen cell load variation. …”
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  6. 6
    Determination of dengue hemorrhagic fever disease factors using neural network and genetic algorithms / Yuliant Sibaroni, Sri Suryani Prasetiyowati and Iqbal Bahari Sudrajat

    Determination of dengue hemorrhagic fever disease factors using neural network and genetic algorithms / Yuliant Sibaroni, Sri Suryani Prasetiyowati and Iqbal Bahari Sudrajat by Yuliant, Sibaroni, Sri Suryani, Prasetiyowati, Iqbal Bahari, Sudrajat

    Published 2020
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  7. 7
    Variational Bayesian inference for exponentiated Weibull right censored survival data

    Variational Bayesian inference for exponentiated Weibull right censored survival data by Jibril Abubakar, Jibril Abubakar, Mohd Asrul Affendi Abdullah, Mohd Asrul Affendi Abdullah, Oyebayo Ridwan Olaniran, Oyebayo Ridwan Olaniran

    Published 2023
    “…The results from the experiments reveal that the Variational Bayesian (VB) approach is better than the competing Metropolis-Hasting Algorithm and the reference maximum likelihood estimates.…”
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  8. 8
    A novel chaotic flower pollination algorithm for global maximum power point tracking for photovoltaic system under partial shading conditions

    A novel chaotic flower pollination algorithm for global maximum power point tracking for photovoltaic system under partial shading conditions by Yousri D., Babu T.S., Allam D., Ramachandaramurthy V.K., Etiba M.B.

    Published 2023
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  9. 9
    The use of radar-rainfall inputs for quantitative precipitation estimation (QPE) in Klang River Basin / Suzana Ramli

    The use of radar-rainfall inputs for quantitative precipitation estimation (QPE) in Klang River Basin / Suzana Ramli by Ramli, Suzana

    Published 2015
    “…Flooding is a natural disaster that often occurs in Malaysia due to its heavy rainfall distribution. Lately, the exceptional amount of rainfall worsens the flood situation. …”
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  10. 10
    Optimisation of fed-batch fermentation process using deep reinforcement learning

    Optimisation of fed-batch fermentation process using deep reinforcement learning by Chai, Wan Ying

    Published 2023
    “…When dealing with model mismatch (±15% parameter variation in critical growth and maximum glucose uptake rate) and process disturbance (±20% deviation in substrate feeding concentration), the proposed algorithm was able to handle the changes with a minor effect on the yeast yield up to 13.78% and 2.52%, respectively, across all different initial condition cases. …”
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  11. 11
    Simulation of the distributed rainfall-runoff process

    Simulation of the distributed rainfall-runoff process by Huang, Yuk Feng, Lee, Teang Shui

    Published 2011
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  12. 12
    Predicting stroke using ant colony optimization algorithm / Azfaruddin Azri and Rizauddin Saian

    Predicting stroke using ant colony optimization algorithm / Azfaruddin Azri and Rizauddin Saian by Azri, Azfaruddin, Saian, Rizauddin

    Published 2023
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  13. 13
    A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing

    A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

    Published 2024
    “…Given the multitude of components to manage, streamflow forecasting is preferable to employ an algorithm with low sensitivity to parameter variations. …”
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  14. 14
    An application of backtracking search algorithm in designing power system stabilizers for large multi-machine system

    An application of backtracking search algorithm in designing power system stabilizers for large multi-machine system by Islam N.N., Hannan M.A., Shareef H., Mohamed A.

    Published 2023
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  15. 15
    Heat transfer through a higher grade Forchheimer porous CuO–H2O-nano-medium confined between non-isothermal moving plates

    Heat transfer through a higher grade Forchheimer porous CuO–H2O-nano-medium confined between non-isothermal moving plates by Memon, M. Asif, Khan, Muhammad Sabeel, Saleem, S., Eldin, S.M., Jacob, Kavikumar

    Published 2023
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  16. 16
    Heat transfer through a higher grade Forchheimer porous CuO–H2O-nano-medium confined between non-isothermal moving plates

    Heat transfer through a higher grade Forchheimer porous CuO–H2O-nano-medium confined between non-isothermal moving plates by Memon, M. Asif, Khan, Muhammad Sabeel, Saleem, S., Eldin, S.M., Kavikumar Jacob, Kavikumar Jacob

    Published 2023
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  17. 17
    Design of QFT-based self-tuning deadbeat controller

    Design of QFT-based self-tuning deadbeat controller by Mansor, Hasmah, Mohd Noor, Samsul Bahari

    Published 2013
    “…The efficiency of the self-tuning QFT based dead-beat controller has been proven from the tests results in terms of controller’s parameters are updated online, less percentage of overshoot and settling time especially when there are variations in the plant. …”
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  18. 18
    Design of QFT-based self-tuning deadbeat controller

    Design of QFT-based self-tuning deadbeat controller by Mansor, Hasmah, Mohd Noor, Samsul Bahari

    Published 2013
    “…The efficiency of the self-tuning QFT based dead-beat controller has been proven from the tests results in terms of controller’s parameters are updated online, less percentage of overshoot and settling time especially when there are variations in the plant.…”
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  19. 19
    Field data-based mathematical modeling by Bode equations and vector fitting algorithm for renewable energy applications

    Field data-based mathematical modeling by Bode equations and vector fitting algorithm for renewable energy applications by Sabry, Ahmad H., Wan Hasan, Wan Zuha, Ab Kadir, M. Zainal A., Mohd Radzi, Mohd Amran, Shafie, Suhaidi

    Published 2018
    “…Four case studies are addressed and compared with several common methods. …”
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  20. 20
    Neural Network Model and Finite Element Simulation of Spring back in Plane-Strain Metallic Beam Bending

    Neural Network Model and Finite Element Simulation of Spring back in Plane-Strain Metallic Beam Bending by Abu Khadra, Fayiz Y. M.

    Published 2006
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