Search Results - (( parameter optimization strategy algorithm ) OR ( parameter simulation study algorithm ))

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  1. 1

    Optimization of milling parameters using ant colony optimization by Mohd Saupi, Mohd Sauki

    Published 2008
    “…The simulation based on ACO algorithm are successful develop and the optimization of parameters values is to maximize the production rate is obtain from the simulation.…”
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    Undergraduates Project Papers
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    Finite impulse response optimizers for solving optimization problems by Tasiransurini, Ab Rahman

    Published 2019
    “…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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    Thesis
  4. 4

    Finite impulse response optimizers for solving optimization problems by Ab Rahman, Tasiransurini

    Published 2019
    “…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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    Thesis
  5. 5

    Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets by Saeed, Sana

    Published 2019
    “…For its fast convergence and for its efficient search procedure, the self-adaptation is proposed in the parameters of the proposed hybrid algorithm. The effectiveness of this algorithm is verified by applying it on the unconstrained and constrained test functions through a simulation study. …”
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    Thesis
  6. 6

    Optimization-based simulation algorithm for predictive-reactive job-shop scheduling of reconfigurable manufacturing systems by Tan, Joe Yee

    Published 2022
    “…Simulation experiments were run using different parameters to analyze the performance of the proposed algorithm with the system. …”
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    Thesis
  7. 7

    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
    “…The orthogonal learning mechanism improves the performance of the original GOOSE algorithm. This FC model uses the root mean squared error as the objective function for optimizing the unknown parameters. …”
    Article
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    Robustness Analysis Of An Optimized Controller Via Particle Swarm Algorithm by Chong, Chee Soon, Ghazali, Rozaimi, Jaafar, Hazriq Izzuan, Syed Hussein, Syarifah Yuslinda, Md Rozali, Sahazati

    Published 2017
    “…The finding shows that the SMC that utilized the PSO algorithm parameters are capable to produce smaller robustness index values, which demonstrated better robustness characteristic in confront with the variation of the system parameter.…”
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    Article
  10. 10

    Optimization of chemotherapy using metaheuristic optimization algorithms / Prakas Gopal Samy by Prakas Gopal , Samy

    Published 2024
    “…Advancing multi-objective optimization techniques for cancer treatment strategies, the study strategically incorporates Swarm Intelligence (SI) and Evolutionary Algorithms (EA). …”
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    Thesis
  11. 11

    A comparative study for parameter selection in online auctions by Gan, Kim Soon

    Published 2009
    “…Hence, this work attempts to improve an existing bidding strategy by taking into accounts the evolution of various model of generic algorithm in optimizing the parameter of the bidding strategies. …”
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    Thesis
  12. 12

    Optimization of operations of reservoir systems for hydropower generation in Tigris River Basin, Iraq by Al-Aqeel, Yousif Hashim Abdullah

    Published 2016
    “…The performances of these two algorithms were evaluated through comparing their optimal values. …”
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    Thesis
  13. 13

    Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar by Md. Rasel, Sarkar

    Published 2019
    “…There is no particular study which focuses on the optimization and prediction of blades parameters using natural inspired algorithms namely Ant Colony Optimization (ACO), Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO) and Adaptive Neuro-fuzzy Interface System (ANFIS) respectively for optimal power coefficient (�436�45D ). …”
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    Thesis
  14. 14

    Energy management strategy of HEV based on simulated annealing by Asrul Sani, Ramli, Muhammad Ikram, Mohd Rashid, Mohd Ashraf, Ahmad

    Published 2020
    “…This work focuses on the optimization of fuel and electrical power consumption in the hybrid electric vehicle (HEV) by utilizing a Simulated Annealing (SA) algorithm. The aim is to find the optimal control parameters of HEV such that the power loss is minimized. …”
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    Article
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    PI controller based genetic algorithm for PV inverter using SPWM technique / Muhammad Hafiz Dzikri Mohammad Salihhuddin by Mohammad Salihhuddin, Muhammad Hafiz Dzikri

    Published 2025
    “…This study focuses on optimizing a three-phase photovoltaic (PV) inverter system using Sinusoidal Pulse Width Modulation (SPWM) with Genetic Algorithm (GA)-optimized Proportional-Integral (PI) controllers. …”
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    Thesis
  17. 17

    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
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    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
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    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
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    An adaptively switching iteration strategy for population based metaheuristics / Nor Azlina Ab. Aziz by Nor Azlina, Ab. Aziz

    Published 2017
    “…Experiments conducted using three parent algorithms namely particle swarm optimization (PSO), which is a popular population-based optimizer with population and individual memories, gravitational search algorithm (GSA), a memoryless young optimizer, and simulated Kalman filter (SKF), a newly introduced optimization algorithm that use population’s memory to guide an agent’s search, show that iteration strategy is an algorithm dependent parameter as well as function dependent. …”
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    Thesis