Abstract Gaussian process (GP) models are widely used to analyze spatially referenced data and predict values at locations without observations. They based on a statistical framework, which enables uncertainty quantification of the model structure predictions. Both evaluation likelihood prediction involve solving linear systems. Hence, computational costs large limit amount that can be handled....

In machine learning, reducing the complexity of a model can help to improve its computational efficiency and avoid overfitting. genetic programming (GP), reduction is often achieved by size evolved expressions. However, previous studies have demonstrated that expression does not necessarily prevent Therefore, this paper uses evaluation time – required evaluate GP on data as estimate complexity....

Currently, the research of emergency supplies distribution and decision models mostly focus on deterministic models and exact algorithm. A few of studies have been done on the multi-level distribution network and matheuristic algorithm. In this paper, random processes theory is adopted to establish emergency supplies distribution and decision model for multi-level network. By analyzing the char...

In this research we tackle the scheduling problem in additive manufacturing for unrelated parallel machines. Both nesting and aspects are considered. Parts have several alternative build orientations. The goal is to minimize total tardiness of parts. We propose a mixed-integer linear programming model which considers subproblem as 2D bin-packing problem, well simplifies 1D problem. computationa...

Abstract We study the numerical simulation of shaken dynamics , a parallel Markovian for spin systems with local interaction and transition probabilities depending on two parameters q J that “tune” geometry underlying lattice. The analysis mixing time Markov chain evaluation spin-spin correlations as functions make it possible to determine in ( ) plane phase curve separating disordered from ord...

in this paper, load and buckling mode of a smart column are presented. the theoretical model is a three-layer piezoelectric composite beam that behaves as an axial actuating mechanism. this actuator consists of an elastic core sandwiched between two piezoelectric active outer layers. the piezoelectric layers are polarized transversely, i.e., the polarization vector is parallel to the applied el...