Conventional, non-Twitter prediction methods predict the winning team around 58percentt of the time.
Both the MAE and RMSE showed that basal area estimates were more accurate than volume estimates for all spatial prediction methods.
Basal area and volume estimates obtained by different spatial prediction methods (Table 9) had average values very close to each other, and were in agreement with the forest inventory estimates (Table 3).
All three methods (local volume equation, FIA-PNW equation, and taper-based volume prediction) over-estimated the logarithmic volume in Douglas-fir trees as indicated by negative bias (Table 9).
Property prediction methods for linear polymers are presented for the amorphous and crystalline volumes, glass transition temperature, solubility parameter and refractive index.
For instance, a study evaluating the influence of six prediction cell sizes (2, 4, 10, 25, 50, and 100 m squares) and two prediction methods (parametric vs. non-parametric) on LiDAR-derived stand-level estimates of total volume found not trend of smaller cell sizes producing lower values of volume, while larger cell sizes tended to give higher estimates [43].
The addition of residual kriging in the basal area and volume mapping (Fig. 7) resulted in a greater difference between maximum and minimum estimated values in all spatial prediction methods.
The combination of spatial prediction methods with residual kriging did not result in relative improvement of spatial prediction accuracy of basal area and volume in all methods assessed in this study, and there is not always a spatial dependency structure in the residuals of a spatial prediction method.
A large-scale experiment to assess protein structure prediction methods.
Protein-coding region identification and gene prediction were conducted using a combination of homology-based prediction, de novo prediction, and transcriptome-based prediction methods.
