Monte Carlo sampling can be used to estimate the solution of path integral control problems, which are a restricted class of nonlinear control problems with arbitrary dynamics and state cost, but with a linear dependence ...

Probabilistic model checking is a powerful tool for analysing probabilistic systems but it can only be efficiently applied to Markov models. Monte Carlo simulation provides an alternative for the generality of stochastic ...

Plant-animal interaction networks provide important information on community organization. One of the most critical assumptions of network analysis is that the observed interaction patterns constitute an adequate sample ...

Establishing a soil sampling plan is one of the most important stages for providing the detailed information required for sustainable land management. This study aims to investigate the most appropriate sampling density ...

Some animals have an important relationship with fungal infections, and searching for pathogens in animal samples may be an opportunity for eco-epidemiological research. Since studies involving wildlife are generally ...

A representative sample is a subset of a population which ensures that those characteristics of the population which are under analysis are represented as completely as possible. There are different ways of estimating a ...

In this work, we propose to leverage the advantages of both the Artificial Neural Network (ANN) based Second Order Reliability Method (SORM) and Importance sampling to yield an Adaptive Importance Sampling based ANN, ...

The green peach aphid Myzus persicae is one of the most important pests in bell pepper crops. Conventional sampling plans are the starting point for the generation of pest control decision-making systems. However, sampling ...