Computational Modeling With Uncertainty of Frequent Users of E-Commerce in Spain Using an Age-Group Dynamic Nonlinear Model With Varying Size Population

Abstract

Electronic commerce (EC) has numerous advantages. It allows saving time when we purchase an item, offers the possibility of review without depending on the schedules of traditional stores, access to a wider variety and quantity of articles, in many cases, with lower prices, etc. Based upon mathematical epidemiology tenets strongly related to social behavior able to describe the influence of peers, in this paper we propose an age-group dynamic model with population varying size based on a system of difference equations to study the evolution of the frequent users of EC over time in Spain. Using data from surveys retrieved from the Spanish National Statistics Institute, we use and design computational algorithms to perform a probabilistic estimation of the model parameters that allow the model output to capture the data uncertainty. Then, we will be able to perform a precise prediction with uncertainty.

Probabilistic calibration and short‐term prediction of the prevalence herpes simplex type 2: A transmission dynamics modelling approach

“…Step 1 has provided a repository whose structure can be seen in Table 3. Then, we apply a selection algorithm inspired on PSO, called PSO selection ( PSO _ S ) 36 . At this point, let us suppose that the repository is made up of H solutions.…”

“…Then, we apply a selection algorithm inspired on PSO, called PSO selection (PSO_S). 36 At this point, let us suppose that the repository is made up of H solutions. The objective of the process is the selection of a reduced set of solutions from the repository, whose model output reproduces, as much accurate as possible, the CI of the data.…”

Advances on Uncertainty Quantification Techniques for Dynamical Systems: Theory and Modelling

“…Uncertainty quantification is an emerging area in mathematics whose main goal is determining information about the uncertainty in the outputs of a mathematical system (usually formulated via dynamical systems), from the available information about the randomness in the inputs. In the setting of mathematical modelling, uncertainty quantification seeks for better explaining the model answer taking into account the variability often met in natural and physical phenomena, [47,66,23,44].…”