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machine learning and deep learning models in matlab 2022b  (MathWorks Inc)


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    MathWorks Inc machine learning and deep learning models in matlab 2022b
    Machine Learning And Deep Learning Models In Matlab 2022b, 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/deep+machine+learning+model/pm40628836-128-5-12
    Average 90 stars, based on 1 article reviews
    machine learning and deep learning models in matlab 2022b - by Bioz Stars, 2026-10
    90/100 stars

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    Article Title: MINT: A toolbox for the analysis of multivariate neural information coding and transmission.
    Article Snippet: MINT is written in MATLAB (version 2018b or newer) and depends on the Statistics and Machine Learning, Optimization, Parallel Computing and Signal Processing Toolboxes.

    Article Title: Supervised machine learning and genotype by trait biplot as promising approaches for selection of phytochemically enriched Rhus coriaria genotypes.
    Article Snippet: Further analysis by supervised machine learning was done through assuming identified phytochemically enriched sumac genotypes (V6, V10, D10, D14, A1, A14, K3, K15, N10, and N11) as a separate group (superior group) and other studied sumac genotypes in another group (inferior group) in MATLAB software.

    Article Title: Evaluating the impact of V-shaped columns on the dynamic behavior of RC buildings on sloped ground
    Article Snippet: demand a deep understanding of seismic code provisions, such as those outlined in IS 1893:2016.. With a growing population and limited flat land, there is an increasing demand for multi-storey buildings on sloping ground.. These buildings pose unique challenges due to their differing structural behaviour compared to those on flat terrain (Kacprzyk, 2014; Tirado-Gutiérrez et al., 2024).

    Article Title: Water temperature modeling through regression and artificial neural network using short-term data for a Philippine River
    Article Snippet: The calculation for the ANN models was performed using the Machine Learning and Deep Learning tool in the MATLAB software.

    Article Title: The solvation thermodynamics of rose acetate in four mixed solvents: Molecular dynamics simulation, molecular conformation analysis, machine learning and solubility prediction
    Article Snippet: The solubility of rose acetate (alpha-(trichloromethyl) benzyl acetate) in four binary solvent mixtures was measured by static gravimetric method at the temperature ranging from 288.15 K to 328.15 K under atmosphere pressure.. The dissolution behavior and solubility prediction were performed through simulations and calculations, using Materials Studio software and Back Propagation Neural Network.. The modified Apelblat equation, λh model, Van’t Hoff equation, and NRTL model were employed to correlate the solubility data respectively.

    Solvent:

    Article Title: MINT: A toolbox for the analysis of multivariate neural information coding and transmission.
    Article Snippet: MINT is written in MATLAB (version 2018b or newer) and depends on the Statistics and Machine Learning, Optimization, Parallel Computing and Signal Processing Toolboxes.

    Article Title: Supervised machine learning and genotype by trait biplot as promising approaches for selection of phytochemically enriched Rhus coriaria genotypes.
    Article Snippet: Further analysis by supervised machine learning was done through assuming identified phytochemically enriched sumac genotypes (V6, V10, D10, D14, A1, A14, K3, K15, N10, and N11) as a separate group (superior group) and other studied sumac genotypes in another group (inferior group) in MATLAB software.

    Article Title: Evaluating the impact of V-shaped columns on the dynamic behavior of RC buildings on sloped ground
    Article Snippet: demand a deep understanding of seismic code provisions, such as those outlined in IS 1893:2016.. With a growing population and limited flat land, there is an increasing demand for multi-storey buildings on sloping ground.. These buildings pose unique challenges due to their differing structural behaviour compared to those on flat terrain (Kacprzyk, 2014; Tirado-Gutiérrez et al., 2024).

    Article Title: Water temperature modeling through regression and artificial neural network using short-term data for a Philippine River
    Article Snippet: The calculation for the ANN models was performed using the Machine Learning and Deep Learning tool in the MATLAB software.

    Article Title: The solvation thermodynamics of rose acetate in four mixed solvents: Molecular dynamics simulation, molecular conformation analysis, machine learning and solubility prediction
    Article Snippet: The solubility of rose acetate (alpha-(trichloromethyl) benzyl acetate) in four binary solvent mixtures was measured by static gravimetric method at the temperature ranging from 288.15 K to 328.15 K under atmosphere pressure.. The dissolution behavior and solubility prediction were performed through simulations and calculations, using Materials Studio software and Back Propagation Neural Network.. The modified Apelblat equation, λh model, Van’t Hoff equation, and NRTL model were employed to correlate the solubility data respectively.



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