Guohe Huang

TL;DR: Comparisons indicated the wavelet network model produced better predictability than the back-forward backpropagation neural network and the multiple regression models in modeling dynamic permeate flux in cross-flow membrane filtration.

TL;DR: Wang et al. as discussed by the authors introduced a clustered polynomial chaos expansion (CPCE) model to reveal random propagation and dynamic sensitivity of uncertainty parameters in hydrologic prediction, which can not only reflect uncertainty propagation in stochastic hydrological simulation, but also have the capability of random forecasting.

TL;DR: The unique role that every sector plays in the socioeconomic system is quantitatively revealed by MDDM, which could guide the relevant policy development at sectorial level.

TL;DR: In this article, a multi-objective stochastic chance constrained programming (MOSCCP) model was developed for assisting local government to design and execute rational energy exploration and management strategies.