In this paper, a maximum entropy-based general framework for probabilistic fatigue damage prognosis is investigated. The proposed methodology is based on an underlying physics-based crack growth model. Various uncertainties from measurements, modeling, and parameter estimations are considered to describe the stochastic process of fatigue damage accumulation. A probabilistic prognosis updating p...

A framework for short-term probabilistic forecasting of watershed flood stage conditions using a distributed rainfall-runoff model is proposed. A stochastic rainfall pattern simulation model capable of generating input for a distributed rainfall-runoff model is developed. Generation of rainfall patterns over a 6-hour period is achieved using a translation vector rainfall forecasting process mod...

Finite element model updating utilizing frequency response functions as inputs is an important procedure in structural analysis, design and control. This paper presents a highly efficient framework that built upon Gaussian process emulation to inversely identify parameters through sampling. In particular, multi-response (MRGP) meta-modeling approach formulated can accurately construct the error...

In this paper, we propose a new model for designing integrated forward/reverse logistics based on pricing policy in direct and indirect sales channel. The proposed model includes producers, disposal center, distributers and final customers. We assumed that the location of final customers is fixed. First, a deterministic mixed integer linear programming model is developed for integrated logistic...

In this study, the finite element model updating was simulated by reducing the stiffness of the members. Due to lack of access to the experimental results, the data obtained from an analytical model were used in the proposed structural damage scenarios. The updating parameters for the studied structures were defined as a reduction coefficient applied to the stiffness of the members. Parameter v...

Nested multi-step stochastic correction offers a possibility to improve updating algorithms for numerical simulations of lattice gauge theories with fermions. The corresponding generalisations of the two-step multi-boson (TSMB) algorithm as well as some applications with hybrid Monte Carlo (HMC) algorithms are considered.

Predicting the effect of persuasion campaigns is difficult, as belief changes may cascade through a network. In recent years, political campaigns have adopted micro-targeting strategies that segment voters into fine-grained clusters for more specific targetting. At present, there is little evidence that explores the efficiency of this method. Through an Agent-Based Model, the current paper prov...

  Performance evaluation of universities is an important issue between researchers. Classic data envelopment analysis (DEA) models with deterministic data have been used by many authors to measure efficiency of universities in different countries. However, DEA with stochastic data are, rarely used to measure efficiency of universities. In this paper, input oriented model in stochastic data env...