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Open image in new window Fig. 4 Fuzzy rule scheme.
The trapezoidal rule scheme does not guarantee the conservation of energy-momentum throughout the duration of the model run.
In contrast to the existing EXP rule scheme, the EXP_MT rules percentage of change lies between 0.07 and 131.98 %.
On the other hand, when the K2 rule scheme faces the strongest attack against the K2 rule, the false alarm rate can be 17.5% with 99% detection rate.
However, when being applied to nonlinear dynamic problems, such as the dynamic fault rupture discussed herein, the trapezoidal rule scheme becomes rather unstable.
Overall, it can be seen that there is a slight improvement in terms of the traffic loss of packets for the sEXP rule scheme in comparison to the EXP rule.
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It is based on a notion of rule instantiation, where the instantiation transforms rule schemes into rule instances by cloning and expansion.
On the other hand, the sEXP rule, E2M, and the EXP_MT rule schemes have much better throughput performance in contrast to the EXP rule.
Table 1 Performance of different color classification schemes (one-stage classification vs. two-stage classification with different decision rules) Scheme Rule D FP One-stage - 96.9 42.0 Two-stage 2/3 96.4 32.0 Two-stage 0.5 96.9 42.2 Two-stage 0.6 96.4 36.1 Two-stage 0.7 96.0 30.1 Two-stage 0.8 94.3 24.7.
Using photography (photoquadrats), all susceptible corals within this area were mapped (similarly to Weinberg [38]) and an X-Y coordinate of the coral's centre within the quadrat was allocated (following the "center rules" scheme of Zvuloni et al. [39]).
To prevent biases related to the boundary effect of the sampling units, only the corals with centers lying within the sampling unit were enumerated (following the "center rules" scheme of Zvuloni et al. [39]).
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