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genetic algorithm (ga) implemented with the global optimization toolbox and the ‘ga’ function  (MathWorks Inc)


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    MathWorks Inc genetic algorithm (ga) implemented with the global optimization toolbox and the ‘ga’ function
    Genetic Algorithm (Ga) Implemented With The Global Optimization Toolbox And The ‘Ga’ Function, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/genetic+algorithm+(ga)+optimization+function/pmc11300869-412-10-23
    Average 90 stars, based on 1 article reviews
    genetic algorithm (ga) implemented with the global optimization toolbox and the ‘ga’ function - by Bioz Stars, 2026-09
    90/100 stars

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    Article Title: Automated Analysis of Relative Fundamental Frequency in Continuous Speech: Development and Comparison of Three Processing Pipelines.
    Article Snippet: Objectives.. Relative fundamental frequency (RFF) estimates laryngeal tension during speech, providing insights into vocal effort.. Current methods to derive RFF from continuous speech require manual processing, hindering large-scale studies with ecologically valid speech productions.

    Article Title: Simultaneous optimized orthogonal matching pursuit with application to ECG compression
    Article Snippet: In our numerical examples we use the off-the-shelf MATLAB implementation of this algorithm [ ].

    Article Title: Deep learning based automated left atrial segmentation and flow quantification of real time phase contrast MRI in patients with atrial fibrillation.
    Article Snippet: The LA was manually contoured on the first time frame to determine a seed region as input for a magnitude intensity-based region growing algorithm (Matlab, Mathworks).

    Article Title: Intact sensorimotor rhythm abilities but altered audiovisual integration in cochlear implant users
    Article Snippet: Tap response latencies were determined from the recorded FSR signal using a threshold-crossing algorithm ( RLW_events_level_trigger function from the LetsWave 6 Matlab toolbox [ ]).

    Article Title: Estimating Mean Viral Load Trajectory From Intermittent Longitudinal Data and Unknown Time Origins
    Article Snippet: Matlab code for the EM‐algorithm and numerical simulations can be accessed at https://github.com/yonatan123/VL‐trajectory .

    Article Title: Equivalent Circuit Modeling and Analysis for Microfluidic Electrical Impedance Monitoring of Single-Cell Growth.
    Article Snippet: The genetic algorithm (GA) in MATLAB was utilized to fine-tune the parameters in the LPM so that they aligned with the experimentally obtained data.

    Article Title: Characterization and mesoscale modeling of an enhanced UHMWPE fabric treated with bis -diazirine: multicriteria crosslinker selection and surrogate-based inverse parameter estimation
    Article Snippet: It is observed that the shear behavior of the material is non-linearly dependent on \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${E}_{2}$$\end{document} E 2 and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$f$$\end{document} f . Fig. 11 The surface model indicating the relationship between a error in tensile loading and b error in shear loading with the friction coefficient and transverse elastic modulus in the untreated fabric In the next step, the genetic algorithm (GA) in MATLAB was utilized to optimize the values of these unknown model parameters.

    Article Title: Comparison between Different Activation Overvoltage Descriptions for Semiempirical Proton-Exchange Membrane Fuel Cell Models
    Article Snippet: To solve this optimization problem, the genetic algorithm (GA) available in MATLAB’s global optimization toolbox is employed.



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