I want to run the NSGA-II in python interface with points generated by Latin hypercube sampling as initial position.. I would like to know how can I use data gain by Latin hypercube sampling gained by ...

A global research team led by scientists from China’s Tianjin Renai College has developed a novel stochastic optimization technique for enhanced dispatching and operational efficiency in PV-powered ...

ABSTRACT: Support vector regression (SVR) and computational fluid dynamics (CFD) techniques are applied to predict the performance of an automotive torque converter in the design process of turbine ...

Abstract: An improved Latin hypercube sampling method is proposed to solve the problems of low computational efficiency and the correlation between computational time, amount of computation, and ...

I've often wished to have a Latin hyper-cube sampling (https://en.wikipedia.org/wiki/Latin_hypercube_sampling) available in Fortran. Given that the sampling was described first in 1979, there is bound ...

Abstract: The present study aims to elaborate on advanced sampling mechanisms employment into bleeding edge machine learning processes. Application of such approaches are considered in two stages.