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Testing a predictive control with stochastic model in a balls mill grinding circuit
(Institute of Electrical and Electronics Engineers Inc., 2014-12)
In this paper, the formulation of a stochastic model and its subsequent incorporation into a predictive control of a balls mill grinding circuit, is presented. The apparition of stochastic variables is a consequence of ...
Optimal reactive power dispatch using stochastic chance-constrained programming
(2012-11-27)
Deterministic Optimal Reactive Power Dispatch problem has been extensively studied, such that the demand power and the availability of shunt reactive power compensators are known and fixed. Give this background, a two-stage ...
Optimal reactive power dispatch using stochastic chance-constrained programming
(2012-11-27)
Deterministic Optimal Reactive Power Dispatch problem has been extensively studied, such that the demand power and the availability of shunt reactive power compensators are known and fixed. Give this background, a two-stage ...
Probabilistic backward location for the identification of multi-source nitrate contamination
(Springer, 2021-01-07)
Nitrate represents the most widespread contaminant in shallow aquifers, especially in urban areas, and poses risks to human health, when the contaminated groundwater is ingested. In urban environments, the release of nitrate ...
Stochastic open-pit mine production scheduling: A case study of an iron deposit
(MDPI, 2020)
Production planning decisions in the mining industry are affected by geological, geometallurgical, economic and operational information. However, the traditional approach to address this problem often relies on simplified ...
Estimation or simulation? That is the question
(SPRINGER, 2008)
The issue of smoothing in kriging has been addressed either by estimation or simulation. The solution via estimation calls for postprocessing kriging estimates in order to correct the smoothing effect. Stochastic simulation ...