Search Results - (( parameter optimization modified algorithm ) OR ( variable prediction using algorithm ))

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  1. 1
    CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING

    CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING by ISLAM, BADAR UL ISLAM

    Published 2017
    “…In the hybrid scheme, the initial parameters of the modified BP neural network are optimized by using the global search ability of genetic algorithm, improved by cat chaotic mapping to enrich its optimization capability. …”
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  2. 2
    Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques

    Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques by Hammid, Ali Thaeer

    Published 2018
    “…Secondly, this approach hybridizing the FA with the rough algorithm (RA), where RA is used to control the steps of randomness for the FA while optimizing the weights of the standard BPNN model. …”
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  3. 3
    Power System State Estimation In Large-Scale Networks

    Power System State Estimation In Large-Scale Networks by NURSYARIZAL MOHD NOR, NURSYARIZAL

    Published 2010
    “…Also the WLS algorithm is modified to include Unified Power Flow Controller (UPFC) parameters. …”
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  4. 4
    Performance assessment of Sn-based lead-free solder composite joints based on extreme learning machine model tuned by Aquila optimizer

    Performance assessment of Sn-based lead-free solder composite joints based on extreme learning machine model tuned by Aquila optimizer by Temitope T., Dele-Afolabi, Masoud, Ahmadipour, Mohamed Ariff, Azmah Hanim, A.A., Oyekanmi, M.N.M., Ansari, Sikiru, Surajudeen, Kumar, Niraj

    Published 2024
    “…An extreme learning machine (ELM) prediction approach refined by Aquila optimizer (AO), a new cutting-edge metaheuristic optimization algorithm was utilized to develop a prediction model for the performance assessment of the developed solder composites. …”
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  5. 5
    Performance assessment of Sn-based lead-free solder composite joints based on extreme learning machine model tuned by Aquila optimizer

    Performance assessment of Sn-based lead-free solder composite joints based on extreme learning machine model tuned by Aquila optimizer by Dele-Afolabi T.T., Ahmadipour M., Azmah Hanim M.A., Oyekanmi A.A., Ansari M.N.M., Sikiru S., Kumar N.

    Published 2025
    “…An extreme learning machine (ELM) prediction approach refined by Aquila optimizer (AO), a new cutting-edge metaheuristic optimization algorithm was utilized to develop a prediction model for the performance assessment of the developed solder composites. …”
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  6. 6
    Information Theoretic-based Feature Selection for Machine Learning

    Information Theoretic-based Feature Selection for Machine Learning by Muhammad Aliyu, Sulaiman

    Published 2018
    “…Three major factors that determine the performance of a machine learning are the choice of a representative set of features, choosing a suitable machine learning algorithm and the right selection of the training parameters for a specified machine learning algorithm. …”
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  7. 7
    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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  8. 8
    Multi-objective optimization of process variables for MWCNT-added electro-discharge machining of 316L steel

    Multi-objective optimization of process variables for MWCNT-added electro-discharge machining of 316L steel by Al-Amin, M., Abdul-Rani, A.M., Ahmed, R., Shahid, M.U., Zohura, F.T., Rani, M.D.B.A.

    Published 2021
    “…The best 21 solution sets predicted through the multi-objective optimization tool called non-dominated sorting genetic algorithm-II (NSGA-II) obeying the set objective functions are proposed which are obtained from the Pareto optimal frontiers. …”
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  9. 9
    Multi-objective optimization of process variables for MWCNT-added electro-discharge machining of 316L steel

    Multi-objective optimization of process variables for MWCNT-added electro-discharge machining of 316L steel by Al-Amin, M., Abdul-Rani, A.M., Ahmed, R., Shahid, M.U., Zohura, F.T., Rani, M.D.B.A.

    Published 2021
    “…The best 21 solution sets predicted through the multi-objective optimization tool called non-dominated sorting genetic algorithm-II (NSGA-II) obeying the set objective functions are proposed which are obtained from the Pareto optimal frontiers. …”
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  10. 10
    Optimization of modified Bouc–Wen model for magnetorheological damper using modified cuckoo search algorithm

    Optimization of modified Bouc–Wen model for magnetorheological damper using modified cuckoo search algorithm by Rosmazi, Rosli, Zamri, Mohamed

    Published 2021
    “…This article presents a new modified cuckoo search algorithm with dynamic discovery probability and step-size factor for optimizing the Bouc–Wen Model in magnetorheological damper application. …”
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  11. 11
    Modified Harmony Search

    Modified Harmony Search by Najihah, Mohamed, Ahmad Lutfi, Amri Ramli, Ahmad, Abd Majid, Abd Rahni, Mt Piah

    Published 2017
    “…A metaheuristic algorithm, called Harmony Search is quite highly applied in optimizing parameters in many areas. …”
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  12. 12
    Hybrid Harmony Search Algorithm with Grey Wolf Optimizer and Modified Opposition-based Learning

    Hybrid Harmony Search Algorithm with Grey Wolf Optimizer and Modified Opposition-based Learning by Alomoush, Alaa A., Alsewari, Abdulrahman A., Alamri, Hammoudeh S., Aloufi, Khalid, Kamal Z., Zamli

    Published 2019
    “…Many variants have been developed to cope with this problem and improve algorithm performance. In this paper, a hybrid algorithm of HS with grey wolf optimizer (GWO) has been developed to solve the problem of HS parameter selection. …”
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  13. 13
    Identification of continuous-time model of hammerstein system using modified multi-verse optimizer

    Identification of continuous-time model of hammerstein system using modified multi-verse optimizer by Most. Julakha, Jahan Jui

    Published 2021
    “…his thesis implements a novel nature-inspired metaheuristic optimization algorithm, namely the modified Multi-Verse Optimizer (mMVO) algorithm, to identify the continuous-time model of Hammerstein system. …”
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  14. 14
    Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study

    Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study by Li Yu Yab, Li Yu Yab, Wahid, Noorhaniza, A Hamid, Rahayu

    Published 2023
    “…—Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO) are well-perform metaheuristic algorithms used by various researchers in solving feature selection problems. …”
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  15. 15
    Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study

    Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study by Li Yu Yab, Li Yu Yab, Wahid, Noorhaniza, A Hamid, Rahayu

    Published 2023
    “…Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO) are well-perform metaheuristic algorithms used by various researchers in solving feature selection problems. …”
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  16. 16
    Application of conjugate gradient approach for nonlinear optimal control problem with model-reality differences

    Application of conjugate gradient approach for nonlinear optimal control problem with model-reality differences by Leong, Wah June, Sie, Long Kek, Teo, Kok Lay, Sim, Sy Yi

    Published 2018
    “…Specifically, the modified model-based optimal control problem is resulted. …”
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  17. 17
    Application of conjugate gradient approach for nonlinear optimal control problem with model-reality difference

    Application of conjugate gradient approach for nonlinear optimal control problem with model-reality difference by Sie, Long Kek, Wah, June Leong, Sy, Yi Sim, Kok, Lay Teo

    Published 2018
    “…Specifically, the modified model-based optimal control problem is resulted. …”
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  18. 18
    Modified multi-verse optimizer for nonlinear system identification of a double pendulum overhead crane

    Modified multi-verse optimizer for nonlinear system identification of a double pendulum overhead crane by Julakha, Jahan Jui, Mohd Ashraf, Ahmad, Muhammad Ikram, Mohd Rashid

    Published 2021
    “…In the HMVOSCA algorithm, the new position updating mechanism of the traditional MVO method is modified based on the sine function and cosine function which is taken from the Sine Cosine Algorithm (SCA). …”
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  19. 19
    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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  20. 20
    Optimal power flow based on fuzzy linear programming and modified Jaya algorithms

    Optimal power flow based on fuzzy linear programming and modified Jaya algorithms by Alzihaymee, Warid Sayel Warid

    Published 2017
    “…A set of modified and novel optimization algorithms are proposed in this thesis to deal with different single and multi-objective OPF problems. …”
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