Montecarlo simulation is a powerful tool to identify influencing factors and intervals in which carry out analytical development tests, although as it mathematical model, must be experimentally confirmed. The results obtained presented the work confirm that this allows previous analysis of sources variability its importance within risk assessment phase. With this, subsequent experimental confir...

The expeditious expansion in the use of inexhaustible recurrent energy resources like Wind turbines and PV cells, in the distribution network has evaluated the need for having rigorous and adequate method of dealing uncertainties correlated with these technologies. In this project the unsymmetrical two point estimate method (US2PEM) is used to approach uncertainties of renewable energy resource...

A fault detection and isolation (FDI) problem is considered for inertial sensors, such as gyroscopes and accelerometers and a new FDI method for double faults is proposed using reduced-order parity vector. The reduced-order parity vector (RPV) algorithm enables us to isolate double faults with 7 sensors. Averaged parity vector is used to reduce false alarm and wrong isolation, and to improve co...

Montecarlo methods can be used to price derivatives for which closed evaluation formulas are not available or di cult to derive. A drawback of the method can be its high computational cost, especially if applied to basket options, whose payo s depend on more than one asset. This article presents two kinds of control variates to reduce variance of estimates, based on unconditional and conditiona...

This paper introduces a new BRDF sampling method with reduced variance, which is based on a hierarchical adaptive PDF. This PDF also is based on rejection sampling with a bounded average number of trials, even in regions where the BRDF exhibits high variations. Our algorithm works in an appropiate way with both physical, analytical and measured reflectance models. Reflected directions are sampl...

We consider the evolution of a parton system which is formed at the central rapidity region just after an ultrarelativistic heavy ion collision. The evolution of the system, which is composed of gluons, quarks and antiquarks, is described by a relativistic Boltzmann equations with collision terms including radiation and retardation effects. The equations are solved by the test particle method u...

In this work we make a first, partial, assessment of the lowto medium-temperature geothermal reserves of Mexico. The assessment covers about 30% of the identified geothermal surface manifestations. For reserve assessment we use the volume method, supplemented with Montecarlo simulations and statistics, in order to quantify the inherent uncertainties. We estimate these reserves as lying between ...

We propose a novel batch active learning method that leverages the availability of high-quality and efficient sequential active-learning policies by approximating their behavior when applied for k steps. Specifically, our algorithm uses MonteCarlo simulation to estimate the distribution of unlabeled examples selected by a sequential policy over k steps. The algorithm then selects k examples tha...

This work presents a novel methodology for the optimal location of reclosers in electric distribution systems. The proposal uses multicriteria analysis to evaluate reliability indicators this level 3 (distribution) by generating scenarios from pseudo-random variables. considered study are System Average Interruption Frequency Index (SAIFI), Duration (SAIDI), Customer (CAIDI), and Energy Not Sup...