Single-objective bounded optimization problems are a type of complex problem that
frequently arises in industry. These problems are often challenging due to the limited internal …

… In the framework of this assumption, the proposed model (without capillarity) allows to
explain the CO 2 vertical stratification in a deep layered aquifer. Then, with this assumption and …

… issues on the significance of creating deep layered architectures in RNN and to characterize
the … The effect of a deep layered organization of RC models is investigated in terms of both …

… -scaled features automatically learned through a deep layered architecture. Different from the
… optimize the feature maps by performing differential evolving iterations on different scales. …

… Differential Evolution Monte Carlo Markov Chain algorithm (DE-MC) was developed by ter
Braak (2006). It combines the differential evolution … a 150 cm-deep layered soil profile, with …

… A DNN is an ANN with a deep layered structure of multiple hidden layers. Compared to
shallow ANNs, the dimension of DNN parameter optimization increases dramatically, and the “…

… Complementary to performance results reported in Table 5, zeta recursive gain ξ, as well
as the nodes (neurons) of the deep-layered structure of second recursive network exerts a …

… Despite tremendous advances made by numerous empirically designed deep networks,
there is still a lack of rigorous theoretical justification of the need or reason for “deep layered” …

Recent deep seismic-reflection profiling has shown a diversity of structure associated with
the lowermost crust. A typically unreflective mantle is overlain by reflections in the lower crust. …

… The geochemical affinity and the intrusion age of the Beaunit deep layered intrusion will
be discussed in the context of the late- to post-collisional evolution of the internal zone of the …