Unveiling current issues in the investigation of highly-active heterogeneous catalysts using machine learning engineering techniques was discussed case oxidative coupling methane with support vector regression and Bayesian optimization.

High- and multi-dimensional array data are becoming increasingly available. They admit a natural representation as tensors call for appropriate statistical tools. We propose new linear autoregressive tensor process (ART) tensor-valued data, that encompasses some well-known time series models special cases. study its properties derive the associated impulse response function. exploit PARAFAC low...

We introduce a novel rule-based approach for handling regression problems. The new methodology carries elements from two frameworks: (i) it provides information about the uncertainty of parameters interest using Bayesian inference, and (ii) allows incorporation expert knowledge through systems. blending those different frameworks can be particularly beneficial various domains (e.g., engineering...

various statistical methods have been proposed in terms of predicting the outcomes of facing special factors. in the classical approaches,  making the probability distribution or known probability density functions is ordinarily necessary to predict the desired outcome. however, most of the times enough information about the probability distribution of studied variables is not available to the ...