Search results for "Stochastic"

Permutation invariant functionals of Lévy processes

2017

Nonlinear response theory for Markov processes II: Fifth-order response functions

2017

The nonlinear response of stochastic models obeying a master equation is calculated up to fifth-order in the external field thus extending the third-order results obtained earlier (G. Diezemann, Phys. Rev. E{\bf 85}, 051502 (2012)). For sinusoidal fields the $5\om$-component of the susceptibility is computed for the model of dipole reorientations in an asymmetric double well potential and for a trap model with a Gaussian density of states. For most realizations of the models a hump is found in the higher-order susceptibilities. In particular, for the asymmetric double well potential model there are two characteristic temperature regimes showing the occurence of such a hump as compared to a …

Supporting group decision makers to locate temporary relief distribution centres after sudden-onset disasters

2020

International audience; In the humanitarian response, multiple decision-makers (DMs) need to collaborate in various problems, such as locating temporary relief distribution centres (RDCs). Several studies have argued that maximising demand coverage, reducing logistics costs and minimising response time are among the critical objectives when locating RDCs after a sudden-onset disaster. However, these objectives are often conflicting and the trade-offs can considerably complicate the situation for finding a consensus.To address the challenge and support the DMs, we suggest investigating the stability of non-dominated alternatives derived from a multi-objective model based on Monte Carlo Simul…

Stochastic Galerkin method for cloud simulation

2018

AbstractWe develop a stochastic Galerkin method for a coupled Navier-Stokes-cloud system that models dynamics of warm clouds. Our goal is to explicitly describe the evolution of uncertainties that arise due to unknown input data, such as model parameters and initial or boundary conditions. The developed stochastic Galerkin method combines the space-time approximation obtained by a suitable finite volume method with a spectral-type approximation based on the generalized polynomial chaos expansion in the stochastic space. The resulting numerical scheme yields a second-order accurate approximation in both space and time and exponential convergence in the stochastic space. Our numerical results…

GIGJ: a crustal gravity model of the Guangdong Province for predicting the geoneutrino signal at the JUNO experiment

2019

Gravimetric methods are expected to play a decisive role in geophysical modeling of the regional crustal structure applied to geoneutrino studies. GIGJ (GOCE Inversion for Geoneutrinos at JUNO) is a 3D numerical model constituted by ~46 x 10$^{3}$ voxels of 50 x 50 x 0.1 km, built by inverting gravimetric data over the 6{\deg} x 4{\deg} area centered at the Jiangmen Underground Neutrino Observatory (JUNO) experiment, currently under construction in the Guangdong Province (China). The a-priori modeling is based on the adoption of deep seismic sounding profiles, receiver functions, teleseismic P-wave velocity models and Moho depth maps, according to their own accuracy and spatial resolution. …

Economic performance and risk of farming systems specialized in perennial crops: An analysis of Italian hazelnut production

2019

Abstract Assessing farm profitability and economic risk is important to support farmers' decisions. Several factors affect yields and product prices, in turn influencing farmers' income level and economic risk. However, the literature has often neglected to explicitly account for the role of product quality. This is particularly important for crops such as hazelnut because farmers' prices vary according to the quality of the harvested product. Furthermore, it seems fundamental to disentangle the role of parameters influencing farm results, noticeably yield, product price and quality. This is because farmers select their risk management tools to satisfy their needs, but these are often suita…

Economic modelling as a tool to support macroalgal bloom management: a case study (Sacca di Goro, Po river delta)

2003

During the last 20, years, intensive mollusk farming has been developed in coastal waters, mostly in sheltered bays and lagoons. Often, mollusk stocks are threatened by frequent anoxic events from macroalgal blooms. Here, a decision support tool is described to select the optimal short-term strategy to control algal biomasses. Even though long-term and detailed studies of the lagoon systems are required to provide reliable, biologically based policies, we have here developed a simplified analysis that overlooks most of the ecological complexity, but explicitly includes environmental variability and uncertainty in parameter estimation in the economic assessment of the performances of differe…

Stochastic models for phytoplankton dynamics in Mediterranean Sea

2016

Abstract In this paper, we review some results obtained from three one-dimensional stochastic models, which were used to analyze picophytoplankton dynamics in two sites of the Mediterranean Sea. Firstly, we present a stochastic advection–reaction–diffusion model to describe the vertical spatial distribution of picoeukaryotes in a site of the Sicily Channel. The second model, which is an extended version of the first one, is used to obtain the vertical stationary profiles of two groups of picophytoplankton, i.e. Pelagophytes and Prochlorococcus, in the same marine site as in the previous case. Here, we include intraspecific competition of picophytoplanktonic groups for limiting factors, i.e.…

Comment on “A simple way to incorporate uncertainty and risk into forest harvest scheduling”

2017

In a recent research article, Robinson et al. (2016) described a method of estimating uncertainty of harvesting outcomes by analyzing the historical yield to the associated prediction for a large number of harvest operations. We agree with this analysis, and consider it a useful tool to integrate estimates of uncertainty into the optimization process. The authors attempt to manage the risk using two different methods, based on deterministic integer linear programming. The first method focused on maximizing the 10th quantile of the distribution of predicted volume subject to area constraint, while the second method focused on minimizing the variation of total quantity of volume harvested sub…

Environmentally‐induced noise dampens and reddens with increasing trophic level in a complex food web

2019

Stochastic variability of key abiotic factors including temperature, precipitation and the availability of light and nutrients greatly influences species’ ecological function and evolutionary fate. Despite such influence, ecologists have typically ignored the effect of abiotic stochasticity on the structure and dynamics of ecological networks. Here we help to fill that gap by advancing the theory of how abiotic stochasticity, in the form of environmental noise, affects the population dynamics of species within food webs. We do this by analysing an allometric trophic network model of Lake Constance subjected to positive (red), negative (blue), and non‐autocorrelated (white) abiotic temporal …