Meta-model sre generally applied to approximate multi-objective optimization, reliability analysis, based design etc., not only in order improve the efficiencies of numerical calculation and convergence, but also facilitate analysis sensitivity. The radial basis function neural network (RBFNN) is meta-model employing hidden layer units output linear units, characterized by relatively fast train...

Smoothed analysis is a framework for analyzing the complexity of an algorithm, acting as a bridge between average and worst-case behaviour. For example, Quicksort and the Simplex algorithm are widely used in practical applications, despite their heavy worst-case complexity. Smoothed complexity aims to better characterize such algorithms. Existing theoretical bounds for the smoothed complexity o...

We study by simulation a mixture of active (run-and-tumble) and passive (Brownian) particles with repulsive exclusion interactions in one dimension, subject to ratchet (smoothed sawtooth) potential. Such potential is known rectify at one-body level, creating net current the `easy direction'. This direction which encounters lower maximum force en route top barrier. The constraint results single-...