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rbf (radial basis kernel) function  (MathWorks Inc)


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    MathWorks Inc rbf (radial basis kernel) function
    Rbf (Radial Basis Kernel) 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/radial+basis+function+kernel/pm40425716-125-4-15
    Average 90 stars, based on 1 article reviews
    rbf (radial basis kernel) function - by Bioz Stars, 2026-09
    90/100 stars

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    other:

    Article Title: Ultra-thin multifocal integral LED-projector based on aspherical microlens arrays
    Article Snippet: Although the LUT generation by RBF method is time consuming (30 seconds in MATLAB for generating a sub-image with resolution of 800×800 pixels).

    Article Title: Radial Basis Functional Model of Multi-Point Dieless Forming Process for Springback Reduction and Compensation
    Article Snippet: After developing the prediction model using RBF as a function of curvature radius, punch holding time, and blank thickness, the study employed genetic algorithm on MATLAB to determine the global optimal value of the given objective.

    Article Title: Selecting Useful Groups of Features in a Connectionist Framework
    Article Snippet: We use the Mathworks neural network toolbox implementations of RBF and MLP.

    Article Title: Differentiation of canine and feline neoplasms using multi-modal imaging and machine learning.
    Article Snippet: Classifier was implemented with RBF (radial basis kernel) function, other hyper-parameters were set default (in Matlab); fitPosterior function was used in the post-processing to obtain classification probabilities.

    Article Title: A comparative study of the scalability of alternative metamodelling techniques
    Article Snippet: Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in the publications on our platform.. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content.. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis.

    Article Title: Computational fluid dynamics analysis and optimisation of polymerase chain reaction thermal flow systems
    Article Snippet: The RBF method uses the Multi-Objective Genetic Algorithm (MOGA) solver in MATLAB, whereas the NN methods use the SciPy.optimization module in Python based on a simple weighting between the competing objectives.

    Article Title: Developing a model to predict the start of combustion in HCCI engine using ANN-GA approach
    Article Snippet: The combustion process in Homogeneous Charge Compression Ignition Engines (HCCI) is one of the new methods of futuristic combustion technologies.. Since there is no direct operator for the start of the combustion (SOC) of these engines, air-fuel mixture properties at the moment of entering the combustion chamber, specifies the ignition timing.. In HCCI engines, the ignition timing is the most crucial factor in determining other engine operating characteristics such as power output, pollution, and fuel consumption.

    Article Title: A Support Vector Machine-Assisted Metabolomics Approach for Non-Targeted Screening of Multi-Class Pesticides and Veterinary Drugs in Maize.
    Article Snippet: Therefore, we chose SVMRFE under RBF to run the program in MATLAB software (Version R2019b).



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    Details of tuning parameters and settings of the optimal models for WQI predicting.

    Journal: Heliyon

    Article Title: Assessing and predicting water quality index with key water parameters by machine learning models in coastal cities, China

    doi: 10.1016/j.heliyon.2024.e33695

    Figure Lengend Snippet: Details of tuning parameters and settings of the optimal models for WQI predicting.

    Article Snippet: SVM , radial basis function kernel, sigma = 0.152, C = 1.

    Techniques: