The relative importance of output objectives and the total amount controlling is compared and the impacts on the regional economy caused by the changes of regulation strategy are also evaluated for updating regulation policy.
More general constraints on the relative importance of output and input weights may be imposed to avoid zero weights and to apply decision maker preferred information to outputs and inputs.
In summary, we conclude on the benefits in the use of remotely sensed data for improved accuracy in energy use and carbon emission calculations, the need for semantic integration of mixed data sources and the importance of output visualisation.
Three fuzzy sets in the form of linguistic weighting variables, which include "Weakly preferred (WP)", "Moderately preferred (MP)" and "Extremely preferred (HP)" were utilized to evaluate the importance of output variables.
However, like in RF conditional relationships are still implicit in the importance value output of cforest.
Towards this end, we examined the 'node purity' importance scores output by RF run with the full 57AA set.
More precisely, the Gini variable importance measure output by the original RF algorithm is strongly biased in favor of predictor variables with many possible splits.
For instance, enlarging the set of species for which habitat areas are calculated would most probably increase the efficiency of silvicultural systems which allow both even-aged and uneven-aged management, especially if the weights of the outputs are constrained to reflect the importance of outputs.
This can be accomplished most easily by appending constraints to the dual side of (2) of the form: γm ≥ μmym/μy ≥ βm, m = 1,..., M. (3) Restrictions (3) place lower and upper bounds on the relative importance of each output (as measured by μm) in total output.
This method includes two steps: a screening step that ranks all model parameters by their importance on model output in order to select the potentially important parameters and a second step that aims to quantify the contribution to the variance of model output by each of the pre-selected parameters and by their interactions.
