Here we propose a novel machine learning method for time series forecasting which is based on the widely-used Least Squares Support Vector Machine (LS-SVM) approach. The objective function of our ...

The Nelder-Mead simplex method for function minimization is a "direct" method requiring no derivatives. The objective function is evaluated at the vertices of a simplex, and movement is away from the ...

Nutrient limitation exerts significant pressure on organisms supporting the trade-off between N cost minimization and increased average mass of amino acids that is a function of increased A+T ...

Advances in control and modulation strategies are needed to promote the adoption of multiphase machines and cater to the evolving requirements of modern industries. In this article, a multisequence ...

In this paper we present some algorithms for minimization of DC function (difference of two convex functions). They are descent methods of the proximal-type which use the convex properties of the two ...