Search Results - (( parameter evaluation tool algorithm ) OR ( simulation optimization method algorithm ))

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  1. 1

    Impact of evolutionary algorithm on optimization of nonconventional machining process parameters by B V, Raghavendra, R Annigiri, Anandkumar, Srikatamurthy, JS

    Published 2025
    “…Using a Python environment, three evolutionary algorithms such as, Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Firefly Algorithm (FA), were simulated to evaluate their effectiveness in minimizing surface roughness (Ra). …”
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    Article
  2. 2

    Fast and optimal tuning of fractional order PID controller for AVR system based on memorizable-smoothed functional algorithm by Ren Hao, Mok, Ahmad, Mohd Ashraf

    Published 2022
    “…Nevertheless, many existing optimization tools for tuning the FOPID controller, which are based on multi-agent based optimization, require large number of function evaluation in their algorithm that could lead to high computational burden. …”
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  3. 3

    Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm by Manoharan P., Ravichandran S., Kavitha S., Tengku Hashim T.J., Alsoud A.R., Sin T.C.

    Published 2025
    “…This approach demonstrates the ability of the GOOSE algorithm to simulate complex systems and enhances the robustness and adaptability of the simulation tool by integrating essential behaviours into the computational framework. …”
    Article
  4. 4

    Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems by Nor Sakinah, Abdul Shukor

    Published 2019
    “…Hence, a memory-based optimization tool has good potential to retain the optimal design parameter during the PID tuning process. …”
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    Thesis
  5. 5

    Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems by Nor Sakinah, Abdul Shukor

    Published 2019
    “…Hence, a memory-based optimization tool has good potential to retain the optimal design parameter during the PID tuning process. …”
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    Thesis
  6. 6

    Data-driven PID controller of wind turbine systems using safe experimentation dynamics algorithm by Islam, Muhammad Shafiqul, Mohd Ashraf, Ahmad, Mohd Riduwan, Ghazali, Mohd Helmi, Suid, Mohd Zaidi, Mohd Tumari

    Published 2024
    “…These results underscore the efficacy of the SEDA method in providing optimal PID control parameters while reducing computational burdens by 52% compared to other multi-agent optimization-based methods.…”
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    Conference or Workshop Item
  7. 7

    Fuzzy clustering method and evaluation based on multi criteria decision making technique by Sameer, Fadhaa Othman

    Published 2018
    “…This proposed algorithm is developed based on heuristic method named modified binary particle swarm optimization (MBPSO) with kernel fuzzy clustering method as a fitness function. …”
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    Thesis
  8. 8

    A memory-guided Jaya algorithm to solve multi-objective optimal power flow integrating renewable energy sources by Ahmadipour M., Ali Z., Ramachandaramurthy V.K., Ridha H.M.

    Published 2025
    “…To ensure fair comparisons, parameter configurations for all algorithms are automated using the parameter tuning tool iterated racing (irace). …”
    Review
  9. 9

    Fast PID tuning of AVR system using memory-based smoothed functional algorithm by Islam, Muhammad Shafiqul, Mohd Ashraf, Ahmad, Hao, Mok Ren, Mohd Helmi, Suid, Mohd Zaidi, Mohd Tumari

    Published 2024
    “…However, existing optimization tools for tuning PID controllers, particularly those based on multi-agent optimization, often involve a large number of function evaluations, resulting in high computational burdens. …”
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    Conference or Workshop Item
  10. 10

    Independent task scheduling algorithms in fog environments from users’ and service providers’ perspectives: a systematic review by Al-Qadhi, Abdulrahman K., Latip, Rohaya, Chiong, Raymond, Athauda, Rukshan, Hussin, Masnida

    Published 2025
    “…To address these issues, a substantial amount of work has been done to determine optimal methods to improve QoS using task scheduling algorithms. …”
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    Article
  11. 11

    Model-free controller design based on simultaneous perturbation stochastic approximation by Mohd Ashraf, Ahmad

    Published 2015
    “…At the same time, it is also worthy to consider an optimization tool for the model-free approach that is simple to understand for engineers and can optimize a large number of control parameters in a fast manner. …”
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    Thesis
  12. 12

    A Novel Hybrid Deep Learning Model Based on Simulated Annealing and Cuckoo Search Algorithms for Automatic Radiomics-Based COVID-19 Diagnosis by Saleh, Basma Jumaa, Omar, Zaid, As’ari, Muhammad Amir, Bhateja, Vikrant, Izhar, Lila Iznita

    Published 2025
    “…To further enhance COVID-19 lesion estimation, novel optimization strategies, including a hybrid simulated annealing-cuckoo search (SA-CS) algorithm, are introduced alongside the original SA method. …”
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    Article
  13. 13

    Data-driven neuroendocrine-pid tuning based on safe experimentation dynamics for control of TITO coupled tank system with stochastic input delay by Mohd Riduwan, Ghazali, Mohd Ashraf, Ahmad, Raja Mohd Taufika, Raja Ismail

    Published 2019
    “…This paper addresses a data-driven neuroendocrine-PID tuning for the control of a two-input-two-output (TITO) coupled tank system with sto-chastic input time delay based on safe experimentation dynamics (SED). The SED algorithm is an optimization method used as data-driven tools to find the optimal control parameters by using the input-output (I/O) data measurement in an actual system. …”
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  14. 14

    Development of data-driven controller for slosh suppression in liquid cargo vehicles by Mohd Falfazli, Mat Jusof, Ahmad, Mohd Ashraf, Raja Ismail, R. M.T., Suid, Mohd Helmi, Saari, Mohd Mawardi

    “…At the same time, it is also worthy to consider an optimization tool for the data-driven approach that is simple to understand for engineers and can optimize a large number of control parameters in a fast manner. …”
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    Research Report
  15. 15

    Prediction Of Petroleum Reservoir Properties Using Nonlinear Feature Selection And Ensembles Of Computational Intelligence Techniques by Anifowose, Fatai Adesina

    Published 2015
    “…A thorough analysis of the comparative results showed that our proposed methods and algorithms outperformed the benchmarks. …”
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    Thesis
  16. 16

    Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani by Ehsan Taslimi , Renani

    Published 2018
    “…To obtain the unknown vector of parameters of the MHTan, three heuristic optimization algorithms are employed to minimize the sum of squared residuals. …”
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    Thesis
  17. 17

    Dynamic investment model for the restructed power market in the presence of wind source by Esfahani, Mohammad Tolou Askari Sedehi

    Published 2014
    “…In the third step, the long term optimal investment strategies of the hybrid wind-thermal investor are determined based on the dynamic programming algorithm by considering the long term states of demand growth and fuel price uncertainties. …”
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    Thesis
  18. 18

    Tubular Linear Switched Reluctance Actuator: Design And Characterization by Yeo,, Chin Kiat

    Published 2019
    “…The investigation is achieved through the simulation using the Finite Element Method (FEM) analysis and the performance is evaluated based on the generated thrust force. …”
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    Thesis
  19. 19

    Energy efficient path reconstruction in wireless sensor network using iPath by Hasan, Sazlinah, Abd, Wamidh Jwdat, Ariffin, Ahmad Alauddin

    Published 2019
    “…To achieve energy efficiency, it compresses the packet information by using GZIP tools in JAVA. Energy efficient iPath (E-iPath) is evaluated with several variations of nodes in WSN deployments as well as large-scale simulations. …”
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    Article
  20. 20

    Optimization of turning parameters using genetic algorithm method by Shah Izwandi, Mohd Zawawi

    Published 2008
    “…The simulation based on Genetic Algorithm are successful develop and the optimum parameters values are obtained from the simulation.…”
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    Undergraduates Project Papers