Search Results - (( parameter optimization modified algorithm ) OR ( variable optimization search 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
    Optimizing n-1 contingency rankings using a nature-inspired modified sine cosine algorithm

    Optimizing n-1 contingency rankings using a nature-inspired modified sine cosine algorithm by Priyadi, Irnanda, Daratha, Novalio, Gunawan, Teddy Surya, Ramli, Kalamullah, Jalistio, Febrian, Mokhlis, Hazlie

    Published 2025
    “…A novel approach utilizing the Modified Sine Cosine Algorithm (MSCA), a nature-inspired metaheuristic optimization technique, is proposed to resolve (N-1) contingency rankings efficiently. …”
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  3. 3
    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
    “…To deal with these problems, this thesis introduces three approved intelligent controllers for hydropower generation. Firstly, a hybrid algorithm namely firefly particle swarm optimization (FPSO) and series division method (SDM) based on the practical swarm optimization and the firefly algorithm is proposed. …”
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  4. 4
    Variable Neighborhood Descent and Whale Optimization Algorithm for Examination Timetabling Problems at Universiti Malaysia Sarawak

    Variable Neighborhood Descent and Whale Optimization Algorithm for Examination Timetabling Problems at Universiti Malaysia Sarawak by Emily Sing Kiang, Siew

    Published 2025
    “…The original WOA is modified by replacing the equations designed for continuous problem domains with local search methods, enhancing its adaptability to discrete optimization problems. …”
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  5. 5
    A variable-capacity-based fuzzy random facility location problem with VaR objective

    A variable-capacity-based fuzzy random facility location problem with VaR objective by Wang, Shuming, Watada, Junzo, Shamsul Bahar, Yaakob, Prof. Madya

    Published 2010
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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
    New global maximum power point tracking and modular voltage equalizer topology for partially shaded photovoltaic system / Immad Shams

    New global maximum power point tracking and modular voltage equalizer topology for partially shaded photovoltaic system / Immad Shams by Immad , Shams

    Published 2022
    “…In terms of controller-based, in this work, a new global maximum power point tracking (GMPPT) algorithm based on a modified butterfly optimization algorithm (MBOA) has been proposed. …”
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  8. 8
    Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data

    Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data by Qadir Saraf, Tara Othman, Fuad, Norfaiza, Md Taujuddin, Nik Shahidah Afifi

    Published 2023
    “…Alternatively, variable length searching enables searching within the variable length of the solution space, which leads to more optimality and less computational load. …”
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  9. 9
    Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data

    Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data by Qadir Saraf, Tara Othman, Fuad, Norfaiza, Md Taujuddin, Nik Shahidah Afifi

    Published 2023
    “…Alternatively, variable length searching enables searching within the variable length of the solution space, which leads to more optimality and less computational load. …”
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  10. 10
    Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data

    Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data by Qadir Sara, Tara Othman, Fuad, Norfaiza, Md Taujuddin, Nik Shahidah Afifi

    Published 2023
    “…Alternatively, variable length searching enables searching within the variable length of the solution space, which leads to more optimality and less computational load. …”
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  11. 11
    Cuckoo search algorithm as an optimizer for optimal reactive power dispatch problems

    Cuckoo search algorithm as an optimizer for optimal reactive power dispatch problems by M. H., Sulaiman, Zuriani, Mustaffa

    Published 2017
    “…This paper presents the application of Cuckoo Search Algorithm (CSA) in optimizing the control variables of power system operation in solving the optimal reactive power dispatch (ORPD) problem. …”
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  12. 12
    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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  13. 13
    Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli

    Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

    Published 2018
    “…To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
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  14. 14
    Hybridizing Invasive Weed Optimization with Firefly Algorithm for Unconstrained and Constrained Optimization Problems

    Hybridizing Invasive Weed Optimization with Firefly Algorithm for Unconstrained and Constrained Optimization Problems by Hyreil A., Kasdirin, N. M., Yahya, M. S. M., Aras, Tokhi, M. O.

    Published 2017
    “…The invasive weed optimization (IWO) algorithm, on the other hand, is effective in accurate global search, but not in local search. …”
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  15. 15
    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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  16. 16
    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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  17. 17
    Vector Evaluated Gravitational Search Algorithm (VEGSA) for multi-objective optimization problems

    Vector Evaluated Gravitational Search Algorithm (VEGSA) for multi-objective optimization problems by Zuwairie, Ibrahim, Badaruddin, Muhammad, Kamarul Hawari, Ghazali, Lim, Kian Sheng, Sophan Wahyudi, Nawawi, Zulkifli, Md. Yusof

    Published 2012
    “…This paper presents a novel algorithm, which is based on Gravitational Search Algorithm (GSA), for multiobjective optimization problems. …”
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  18. 18
    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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  19. 19
    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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  20. 20
    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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