The methodology is independent of the model class, applicable to all black box models, and improves prediction performance for a variety of data in several industrial application areas.
The topographical factor in three classes is applicable in Tennessee Valley.
Tree species with DBH >3 cm found within the quadrat were classified according to DBH classes as applicable.
Sound classes are applicable for newly designed multi-storey dwellings, double-apartments, blocks of multifamily housing, and some non- residential buildings with noise-sensitive indoor environment.
Although the latter two classes are applicable to genome-scale promoter sequences in principle, the high computational cost prohibits application of the first class to large-scale data, despite the fact that motif discovery is the only way if we have no prior knowledge of other species or known motifs.
The result provides a motivation to investigate thermoelastic materials as a new class of applicable materials.
While aiming at a large class of applicable systems, the code also strives for ease-of-use, efficiency, and modularity for the implementation of additional features.
A crucial point is that both, the best linear model and the modeling error, are determined for a specified region of operation, thus significantly increasing the class of applicable nonlinear systems.
The function class is applicable to any positive cost variable and is designed to be: (i) monotonically decreasing, (ii) to have decreasing marginal sensitivity with respect to cost, and (iii) to be differentiable at every point.
The evaluation is performed on a servo-hydraulic vibration exciter by subjecting the seat-damper combinations to a transient excitation with dominant frequency close to that of the seat and continuous random excitation class EM1 applicable to earth-moving machinery, and a more severe excitation realized by amplifying the EM1 excitation by 150%.
