Abstract Hydrological simulation has long been a challenge because of the computationally intensive and expensive nature complex hydrological models. In this paper, surrogate modelling (SM) framework is presented based on Hadoop cloud for approximating The substantial model runs required by design experiment (DOE) SM were solved using cloud. Polynomial chaos expansion (PCE) was fitted verified ...

82 LLE Review, Volume 78 Direct-drive inertial confinement laser fusion is accomplished by uniformly illuminating spherical fuel-bearing targets with high-power laser beams, ablatively driving implosions that result in large increases in density and temperature. Current large laser systems such as the University of Rochester’s OMEGA laser, which is capable of both directand indirectdrive implos...

Particle swarm optimization (PSO) is a population-based, heuristic minimization technique that is based on social behavior. The method has been shown to perform well on a variety of problems including those with nonconvex, nonsmooth objective functions with multiple local minima. However, the method can be computationally expensive in that a large number of function calls is required to advance...

Congestion management in electricity markets is traditionally done using deterministic values of power system parameters considering a fixed network configuration. In this paper, a stochastic programming framework is proposed for congestion management considering the power system uncertainties. The uncertainty sources that are modeled in the proposed stochastic framework consist of contingencie...

This paper discussed possible application of soft computing methods in uncertainty management of the HR component in steel industry during automation period. It explained the importance of HR and the concept of uncertainty management. Then it discussed what to look in soft computing for uncertainty management. Keywords-HR, Soft Computing, space mapping, surrogate model, uncertainty management

Particle swarm optimization (PSO) is a population-based, heuristic minimization technique that is based on social behavior. The method has been shown to perform well on a variety of problems including those with nonconvex, nonsmooth objective functions with multiple local minima. However, the method can be computationally expensive in that a large number of function calls is required to advance...

In the light of increasing volatility in electricity price and availability, demand side management (DSM), which refers to the active management of electricity consumption, has become crucial for the economic performance of power-intensive industries. Due to its time-sensitive nature, DSM is a challenge for industrial plants; however, it can also be an opportunity if sufficient process flexibil...