This paper compares the performance, in terms of convergence rates and precision of the estimates, for six Monte Carlo Simulation sampling methods: Quasi-Monte Carlo using Halton, Sobol, and Faure numeric sequences; Descriptive Sampling, based on the use of deterministic sets and Latin Hypercube Sampling, based on stratified numerical sets. Those methods are compared to the classical Monte Carl...

Small underwater vehicles have unique advantages in ocean exploration. The resistance and volume of a vehicle are key factors affecting its operation time underwater. This paper aims to develop an effective method obtain the optimal hull shape small using Kriging-based response surface (RSM) multi-objective optimization algorithm. Firstly, hydrodynamic performance is numerically investigated co...

We develop strategies for integrated use of certain well-known variance reduction techniques to estimate a mean response in a finite-horizon simulation experiment. The building blocks for these integrated variance reduction strategies are the techniques of conditional expectation, correlation induction (including antithetic variates and Latin hypercube sampling), and control variates; and all p...

Valuation and risk management of large portfolios of variable annuity policies are a big challenge to insurance companies because pricing a large portfolio of variable annuity policies is a time consuming task. Recently, a method based on clustering and kriging has been proposed to address the computational problem arising from this area. In this method, the value of the portfolio is estimated ...

Generalist predators consist an important component of ecosystem which may act as a biocontrol agent and influence the dynamics significantly. In this paper, we have studied effect delayed logistic growth prey species with group defence behaviour. The Lyapunov stability criteria for interior equilibrium point is derived. Also, condition Hopf bifurcation are obtained. length delay also estimated...

We propose use of Latin Hypercube Sampling to create a synthetic data set that reproduces many of the essential features of an original data set while providing disclosure protection. The synthetic micro data can also be used to create either additive or multiplicative noise which when merged with the original data can provide disclosure protection. The technique can also be used to create hybr...

Adhesively bonding has been increasingly used for numerous industrial applications to meet the high demand lightweight and safer structures. Debonding of adhesively bonded joints is a typical mixed mode failure process. It highly depended on interactional effects material properties geometric definitions constituents, which very complicated. The existing studies in identifying fracture modes ba...

Quantifying and propagating uncertainties in structural response is critical to robust performance-based seismic assessments. This paper evaluates the influence of model parameter uncertainty on limit state assessment controlled rocking steel braced frames (CRSBFs). The dead load frame, fuse yield strength, initial post-tension (PT) force strength frame elements are random variables considered....

Many computational problems in statistics can be cast as stochastic programs that are optimization problems whose objective functions are multi-dimensional integrals. The sample average approximation method is widely used for solving such a problem, which first constructs a sampling-based approximation to the objective function and then finds the solution to the approximated problem. Independen...