First, the similarity of ECFP4 fingerprints based on Dice similarity metric [31] is employed to calculate distances between molecular objects and then the MinMax algorithm is applied to select a subset of diverse molecules based on the aforementioned distances.
Figure 11 shows the plot of the aforementioned minimum distance versus the number of learning steps.
Table 1 shows the relative percentage difference (RPD) of CA, which was calculated by BPD over the three distance metrics aforementioned.
As aforementioned, the mean Mn-Mn distance is 11.4 nm, thus, all the characteristic lengths, e.g., wire diameter and mean distances, are of the same order of magnitude.
d is the minimum distance between the aforementioned nearest neighbor and the extreme points of its line cluster.
Besides that, n 0 is the additive white Gaussian noise (AWGN) with mean power, Ω 0. In terms of system channels, the channel gains are denoted as h X,h Y, and h Z for the link from UE1 to R, and R to UE2, UE3, respectively, while the corresponding channel gain for the P2P communication between UE2 and UE3 is h W. Furthermore, r k is the distances for the aforementioned links, where k∈{X,Y,Z,W}.
As aforementioned, lateral deviation in this case is meant to be the distance of the driver's vehicle from the middle of his/her traffic lane.
As aforementioned, a gene associates with a vector and the similarity of two genes can be estimated by the distance between the two vectors.
Take the aforementioned gull.
