Search Results - (( parameter optimization method algorithm ) OR ( a validation study algorithm ))

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    An improved method using fuzzy system based on hybrid boahs for phishing attack detection by Noor Syahirah, Nordin

    Published 2022
    “…Moreover, Butterfly Optimization Algorithm and Harmony Search Algorithm were combined as optimization method led to a new method named BOAHS. …”
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    Impact of evolutionary algorithm on optimization of nonconventional machining process parameters by B V, Raghavendra, R Annigiri, Anandkumar, Srikatamurthy, JS

    Published 2025
    “…The results of the three algorithms were validated through a benchmark study employing the Genetic Algorithm. …”
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    Estimation of photovoltaic models using an enhanced Henry gas solubility optimization algorithm with first-order adaptive damping Berndt-Hall-Hall-Hausman method by Ramachandran, Murugan, Sundaram, Arunachalam, Ridha, Hussein Mohammed, Mirjalili, Seyedali

    Published 2024
    “…A reliable methodology is essential for accurately estimating the parameters of PV models, enabling reliable performance evaluations, effective control studies, accurate analysis of partial shading effects, and optimal optimization of Photovoltaic (PV) systems. …”
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    Characterization of PV panel and global optimization of its model parameters using genetic algorithm by Ismail, M.S., Moghavvemi, Mahmoud, Mahlia, T.M.I.

    Published 2013
    “…This paper details an improved modeling technique for a photovoltaic (PV) module; utilizing the optimization ability of a genetic algorithm, with different parameters of the PV module being computed via this approach. …”
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    Hybrid Artificial Bees Colony Algorithms For Optimizing Carbon Nanotubes Characteristics by Mohammad Jarrah, Mu'ath Ibrahim

    Published 2018
    “…Optimization is a crucial process to select the best parameters in single and multi-objective problems for manufacturing process.However,it is difficult to find an optimization algorithm that obtain the global optimum for every optimization problem.Artificial Bees Colony (ABC) is a well-known swarm intelligence algorithm in solving optimization problems.It has noticeably shown better performance compared to the state-of-art algorithms.This study proposes a novel hybrid ABC algorithm with β-Hill Climbing (βHC) technique (ABC-βHC) in order to enhance the exploitation and exploration process of the ABC in optimizing carbon nanotubes (CNTs) characteristics.CNTs are widely used in electronic and mechanical products due to its fascinating material with extraordinary mechanical,thermal,physical and electrical properties. …”
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    A comparative study of evolutionary algorithms and adapting control parameters for estimating the parameters of a single-diode photovoltaic module's model by Muhsen D.H., Ghazali A.B., Khatib T., Abed I.A.

    Published 2023
    “…Algorithms; Diodes; Errors; Iterative methods; Least squares approximations; Mean square error; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Coefficient of determination; Differential Evolution; Electromagnetism-like algorithm; Hybrid evolutionary algorithm; Photovoltaic; Photovoltaic modules; Root mean square errors; Single-diode models; Evolutionary algorithms; algorithm; comparative study; electromagnetic method; estimation method; experimental design; numerical method; parameterization; performance assessment; photovoltaic system…”
    Article
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    Thin Film Roughness Optimization In The Tin Coatings Using Genetic Algorithms by Fauzi, Nur Faiqah, Mohamad Jaya, Abdul Syukor, Mohammad Jarrah, Mu’ath Ibrahim, Akbar, Habibullah

    Published 2017
    “…Genetic algorithms were used in the optimization work of the coating process to optimize the coating roughness parameters. …”
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    Investigation of Meta-heuristics Algorithms in ANN Streamflow Forecasting by Wei Y., Hashim H., Chong K.L., Huang Y.F., Ahmed A.N., El-Shafie A.

    Published 2024
    “…The deterministic approach, which utilizes the gradient information in the search process, is prone to trapping at local minima, primarily due to the presence of saddle points and local minima in the non-convex objective function of an artificial neural network (ANN). This study investigated the efficacy of a hybrid model that adopted a meta-heuristic algorithm (MHA) as an optimizer to extend the training ANN method, from a gradient-based to a stochastic population-based approach for streamflow forecasting. …”
    Article
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    Improved dung beetle optimization algorithm and finite element analysis for spindle optimization by Haohao, Ma, As’arry, Azizan, Xuping, Wu, Ismail, Mohd Idris Shah, Ramli, Hafiz Rashidi, Saad, Mohd Sazli, Delgoshaei, Aidin

    Published 2024
    “…The study demonstrates the reliability and effectiveness of the proposed IDBO algorithm in conjunction with FEA, providing a versatile framework for engineering optimization.…”
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    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
    “…In order to validate the proposed algorithm, a number of experiments using various datasets were conducted and compared the outcomes with different�state-of-the-art algorithms. …”
    Article
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    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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    Collaborative simulated annealing genetic algorithm for geometric optimization of thermo-electric coolers by Khanh, D.V.K., Vasant, P.M., Elamvazuthi, I., Dieu, V.N.

    Published 2016
    “…In this chapter, the technical issues of TECs were discussed. After that, a new method of optimizing the dimension of TECs using collaborative simulated annealing genetic algorithm (CSAGA) to maximize the rate of refrigeration (ROR) was proposed. …”
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    Parameters extraction of double diode photovoltaic module's model based on hybrid evolutionary algorithm by Muhsen D.H., Ghazali A.B., Khatib T., Abed I.A.

    Published 2023
    “…Algorithms; Diodes; Errors; Extraction; Iterative methods; Mean square error; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Differential evolution algorithms; Diode modeling; Electromagnetism-like algorithm; Fast convergence speed; Hybrid evolutionary algorithm; IV characteristics; Photovoltaic model; Root mean square errors; Evolutionary algorithms…”
    Article
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    Extraction of photovoltaic module model's parameters using an improved hybrid differential evolution/electromagnetism-like algorithm by Muhsen D.H., Ghazali A.B., Khatib T., Abed I.A.

    Published 2023
    “…Algorithms; Evolutionary algorithms; Mean square error; Optimization; Parameter estimation; Photovoltaic cells; Coefficient of determination; DEAM; Five parameters; Hybrid differential evolution; Improved differential evolutions; IV characteristics; Photovoltaic modules; Root mean square errors; Iterative methods; algorithm; artificial intelligence; electromagnetic method; error analysis; experimental study; photovoltaic system…”
    Article
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    Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed by Borujeni, Sattar Chavoshi

    Published 2012
    “…This approach was based on fuzzy expert system (FES) using Fuzzy Toolbox of MATLAB software. Genetic algorithm (GA) was employed to adjust parameters of FES and optimize the system. …”
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    Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm by Alyaa Ghazi Mohammed, Mohd Zakree Ahmad Nazri

    Published 2025
    “…This study introduces a multi-layer perceptron neural network (MLP) algorithm tailored to predict the likelihood of coronary artery disease (CAD) onset by meticulously analyzing relevant risk factors derived from the Z-Alizadeh Sani dataset, a comprehensive repository of clinical data that captures diverse patient profiles and diagnostic indicators. …”
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