Stochastic Reservoir

Stochastic Synthesis of Drouths for Reservoir Storage Design (RESEARCH NOTE).

Time series techniques are applied to Ghara-Aghaj flow records, in order to generate forecast values of the mean monthly river flows. The study of data and its correlogram shows the effect of seasonality and provide no evidence of trend. The autoregressive models of order one and two (AR1, AR2), moving average model of order one and ARMA (1,1) model are fitted to the stationary series, where th...

STOCHASTIC SIMULATION And RESERVOIR MODELING WORKFLOW

Reservoir Computing with Stochastic Bitstream Neurons

Reservoir Computing (RC) [6], [5], [9] is a computational framework with powerful properties and several interesting advantages compared to conventional techniques for pattern recognition. It consists essentially of two parts: a recurrently connected network of simple interacting nodes (the reservoir), and a readout function that observes the reservoir and computes the actual output of the syst...

Reservoir Computing using Stochastic p-Bits

We present a general hardware framework for building networks that directly implement Reservoir Computing, a popular software method for implementing and training Recurrent Neural Networks and are particularly suited for temporal inferencing and pattern recognition. We provide a specific example of a candidate hardware unit based on a combination of soft-magnets, spin-orbit materials and CMOS t...

Parallel Simulated Annealing for Stochastic Reservoir Modeling

Simulatedannealing (SA) Wutiques have shown great potential to generate geologically realistic permeability fields by combining data from many sources, such as well logs, cores, and tracer tests. However, the application of SA in reservoir description and simulation is limited owing to its prohibitively large computational time requirement, even on modern MqXWornputem. This paper introduces an ...