
www.iser.essex.ac.uk/pubs/workpaps/pdf/200410.pdf
Figure 3: Distribution of the Fuzzy Monetary index Ij , survey A. w1 w2 w3 w4 w5 w6 w7 w8 w9 w10 >1


www.unisi.it/ricerca/dip/dmq/verma/Reports/%5B13%5D%20Betti_Verma%20WP49Siena.pdf
in poverty during past 5 years Fuzzy monetary poverty measure (FM) mean years ... j w j .T j . T Σ j wj T = the distribution of that time according to the number of years ... Table 10 Distribution of the population according to the number of years in poverty during past 5 years Conventional monetary poverty measure mean years


www.faronet.it/sipi/2007/novdic/pdf/tarditi_ing.pdf
GRAPH 11 FUZZY MONETARY (FM) AND FUZZY SUPPLEMENTARY (FS) FM (OPc) FS (OPc) FS (OP) FM (OP) ... actually represents the distribution of the individual membership values given by the sample distribution, as the increase in FM levels within the [0.9, 1] interval ... analysis, but the FS presents a positively skewed distribution, with few individuals


www.upit.ro/ccma/EDEN/docs/RCAM%20Journal%202%20EDEN%20II.pdf
Triangular fuzzy numbers The total cost estimation results are shown in Table 7 in the case of triangular fuzzy input variables. The term “code” refers to the cost ... approach to compare with triangular fuzzy approach. In order to compare on the basis


www.cbmjournal.com/content/pdf/1750068067.pdf
were reduced by the skewed distribution of the field data (see Figure 1), which focused


www.undppovertycentre.org/mdpoverty/papers/Achille_embargo.pdf
ECHP wave Fuzzy monetary (FM) poverty rate Italy NORDOVEST NORDEST CENTRO SUD ISOLE 8 ECHP waves w1 w2 w3 w4 w5 w6 w7 w8 FM/H FM headcount ratio (conventional monetary poverty rate) fuzzy measure of monetary poverty rate ('Fuzzy Monetary') mean ... Macroregions with low levels of monetary poverty indicate a higher level of nonmonetary deprivation compared to their level of monetary poverty. Overall ... Returning to Table 7, the last column of the table shows Manifest deprivation index


radiographics.rsna.org/content/22/4/963.full.pdf
. This classiﬁer combines the features into a single index as follows: On the basis of training ... the shape index, gradient concentration, DGC, CT values, and gradient and variance of CT values was particularly effective in this setting. Figure 15 shows the distribution


radiographics.rsnajnls.org/cgi/reprint/22/4/963.pdf
. This classiﬁer combines the features into a single index as follows: On the basis of training ... the shape index, gradient concentration, DGC, CT values, and gradient and variance of CT values was particularly effective in this setting. Figure 15 shows the distribution


www.enggjournals.com/ijcse/doc/IJCSE120403005.pdf
Hence the fuzzy optimal solution in terms of location index and fuzziness index is given by x11 3, 33r, 33r , x 23 3, 55r, 6 6r x 24 4, 2 2r, 4 4r , x 31 1, 55r, 6 6r x 32 (3, 5 5r, 2 2r) , x 33 ... Hence the initial fuzzy transportation cost by the proposed method = 3, 55r, 55r 3, 33r, 33r + + 7, 55r, 6 6r 1, 55r, 6 6r + 5, 55r, 55r ... 15+16+7+15+5, 55r, 66r) = Rs. (67, 55r, 66r) The corresponding fuzzy optimal


www.marama.org/publications_folder/reports/marama_pm2.5forecasting_FINALrpt_111004.pdf
Table 53. Evaluation Metrics for CART Historical Period Evaluation The metrics are: Accuracy (Acc), FAR (False Alarm Rate), DetP (Probability of Detection), CSI (Critical Success Index), and Bias. Days / USG Days Strict Evaluation Fuzzyborder Evaluation
