Probability and the stochastic processes theory, joint to the mathematical modeling and the respective computational support are clearly important work tools to tackle complex systems, which has been ...
Experimental results show that the models constructed by the proposed method not only maintain geological semantic consistency and coherence but also accurately characterize the spatial distribution ...
Hydrological Model (Berkeley). This project implements the underground (stochastic) hydrological model (in Python) that was developed during my postdoctoral tenure at the Dept. of Earth & Planetary ...
This project aims at developing mathematical statistics and probability theory to provide methodologies for modeling and analysis of complex random systems. Statistical methods enable analysis of ...
1 Civil, Environmental and Architectural Engineering, University of Colorado Boulder, Boulder, CO, USA, 2 Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado ...
Abstract: Although various approaches have been reported for forecasting aviation safety risks, they frequently fail to fully consider the stochastic nature and complex interrelations of numerous real ...
Abstract: Distributed photovoltaic (PV), charging piles, and residential electricity use have an increasing problem of heavy overloading of distribution transformers due to stochastic uncertainty in ...
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