Search Results - (( parameter optimization based algorithm ) OR ( parameters variation tool algorithm ))

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  1. 1
    An analysis of the parameter modifications in varieties of harmony search algorithm

    An analysis of the parameter modifications in varieties of harmony search algorithm by Mansor, N. F., Abal Abas, Zuraida, Abdul Rahman, Ahmad Fadzli Nizam, Shibghatullah, Abdul Samad, Safiah , Sidek

    Published 2014
    “…A Harmony Search (HS) algorithm is a population based-meta-heuristics approach that is superior in solving diversified and large scale optimization problems. …”
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  2. 2
    An analysis of the parameter modifications in varieties of harmony search algorithm

    An analysis of the parameter modifications in varieties of harmony search algorithm by Nur Farraliza, Mansor, Zuraida, Abal Abas, Ahmad Fadzli Nizam, Abdul Rahman

    Published 2014
    “…A Harmony Search (HS) algorithm is a population based-meta-heuristics approach that is superior in solving diversified and large scale optimization problems. …”
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  3. 3
    Data Analysis and Machine Learning Algorithms Evaluation for Bioliq AI-based Predictive Tool

    Data Analysis and Machine Learning Algorithms Evaluation for Bioliq AI-based Predictive Tool by Samuel Simbine, Augusto

    Published 2019
    “…This final year project identified relevant parameters through literature research, analysis and expert interview, and evaluated different machine learning algorithms and identified linear regression as the most applicable and efficient with its R-square of 0.8015, qualifying it to be used for the development of a hybrid model for the AI-based tool for predictive process optimization for chemical plants.…”
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  4. 4
    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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  5. 5
    Fast and optimal tuning of fractional order PID controller for AVR system based on memorizable-smoothed functional algorithm

    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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  6. 6
    Design optimization of valve timing at various engine speeds using Multi-Objective Genetic Algorithm (MOGA)

    Design optimization of valve timing at various engine speeds using Multi-Objective Genetic Algorithm (MOGA) by Mohiuddin, A. K. M., Ashour, Ahmed Aly Ibrahim Shaaban, Yap, Haw Shin

    Published 2008
    “…This paper aims to demonstrate the effectiveness of Multi- Objective Genetic Algorithm Optimization and its robust practical application on the automobile engine valve timing where the variation of performance parameters required for finest tuning to obtain the optimal engine performances. …”
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    Proceeding Paper
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  7. 7
    Designing of prediction model for parameter optimization in cnc machining based on artificial neural network / Armansyah ... [et al.]

    Designing of prediction model for parameter optimization in cnc machining based on artificial neural network / Armansyah ... [et al.] by Armansyah, Puji, Muhammad Nurul, Mardhani, Muhammad Destri, Suartana, I Putu Eka, Desmawati, Ferdyanto, Kusumah, Muhammad Afiff, Yafi, Muhammad Umar, Saedon, Juri

    Published 2025
    “…These outputs were then utilized to train an ANN prediction model based on a feed-forward backpropagation (FFBP) algorithm. …”
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  8. 8
    Sensor-less vector control using adaptive observer scheme for controlling the performance of the induction motor / Mazhar Hussain Abbasi

    Sensor-less vector control using adaptive observer scheme for controlling the performance of the induction motor / Mazhar Hussain Abbasi by Mazhar, Hussain Abbasi

    Published 2013
    “…Sensorless vector control technique using adaptive observer scheme is being used to control the performance of induction motor which is demonstrated by the help of matlab/simulink software; a suitable tool for vector control of AC motor. Simulation is done by using the observer which uses optimal feedback gain as an example of process from algorithm design to verification of logic. …”
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  9. 9
    Model-based hybrid variational level set method applied to object detection in grey scale images

    Model-based hybrid variational level set method applied to object detection in grey scale images by Wang, Jing

    Published 2024
    “…This algorithm leverages an improved multi-scale mean filter to mitigate grayscale inhomogeneity while reducing the impact of scale parameter selection. …”
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  10. 10
    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
    “…Then, design of experiments is used to examine the sensitivity of the parameters of each solving algorithm using Taguchi method. …”
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  11. 11
    Green network planning and operational power consumption optimization in LTE-A using artificial intelligence

    Green network planning and operational power consumption optimization in LTE-A using artificial intelligence by Al-Samawi, Aida Ismail Ahmed

    Published 2015
    “…The second stage of the developed algorithm optimizes the average number of relay station per base station and their distance from the respective base station to meet the capacity constraint of the network operator. …”
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  12. 12
    Global Algorithms for Nonlinear Discrete Optimization and Discrete-Valued Optimal Control Problems

    Global Algorithms for Nonlinear Discrete Optimization and Discrete-Valued Optimal Control Problems by Woon, Siew Fang

    Published 2009
    “…One of the more recent global optimization tools in the area of discrete optimization is known as the discrete filled function method. …”
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  13. 13
    Using piecewise affine PID control scheme for double pendulum overhead crane

    Using piecewise affine PID control scheme for double pendulum overhead crane by M. I. F., Mohd Haniff, Mohd Ashraf, Ahmad, Mohd Helmi, Suid, Mohd Falfazli, Mat Jusof, Ahmad Nor Kasruddin, Nasir, Mohd Zaidi, Mohd Tumari

    Published 2019
    “…A Safe Experimentation Dynamics (SED) algorithm is utilized as a model-free optimization tool to find the optimal PA-PID controller parameters such that the integral square of error and input are reduced. …”
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  14. 14
    Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani

    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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  15. 15
    Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems

    Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems by Kek, Sie Long

    Published 2011
    “…The main idea is the integration of optimal control and parameter estimation. In this work, a simplified model-based optimal control model with adjustable parameters is constructed. …”
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  16. 16
    On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing

    On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing by Kamal Z., Zamli, Alsariera, Yazan A., Nasser, Abdullah B., Alsewari, Abdulrahman A.

    Published 2015
    “…In doing so, this paper reviews two existing parameter free optimization algorithms involving Teaching Learning Based Optimization (TLBO) and Fruitfly Optimization Algorithm (FOA) in an effort to promote their adoption for CIT.…”
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  17. 17
    Finite impulse response optimizers for solving optimization problems

    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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  18. 18
    Finite impulse response optimizers for solving optimization problems

    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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  19. 19
    LS-SVM Hyper-parameters Optimization Based on GWO Algorithm for Time Series Forecasting

    LS-SVM Hyper-parameters Optimization Based on GWO Algorithm for Time Series Forecasting by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, M. N. M., Kahar

    Published 2015
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  20. 20
    Enhanced gravitational search algorithm for nano-process parameter optimization problem / Norlina Mohd Sabri

    Enhanced gravitational search algorithm for nano-process parameter optimization problem / Norlina Mohd Sabri by Mohd Sabri, Norlina

    Published 2020
    “…Based on the capabilities of the metaheuristic algorithms, this research is proposing the enhanced Gravitational Search Algorithm (eGSA) to solve the nano-process parameter optimization problem. …”
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