## [1] 14
## [1] 7
## [1] 14
## [1] 9
Unidade Análise | Freq | Perc |
---|---|---|
Block | 4 | 9.523810 |
Cluster | 16 | 38.095238 |
Counties | 1 | 2.380952 |
Grid Cells | 4 | 9.523810 |
LIXEL | 4 | 9.523810 |
Segments and Junctions | 12 | 28.571429 |
Uninformed | 1 | 2.380952 |
Grupamento | Unidade Análise | Freq | Perc |
---|---|---|---|
Beta-binomial screening | Segments and Junctions | 1 | 2.380952 |
Black Spots offically | Uninformed | 1 | 2.380952 |
Cells | Grid Cells | 4 | 9.523810 |
City Limits | Counties | 1 | 2.380952 |
Community Census | Block | 4 | 9.523810 |
DBSCAN | Cluster | 1 | 2.380952 |
Firefly Algorithm | Cluster | 1 | 2.380952 |
Gaussian Mixture Models GMM | Cluster | 1 | 2.380952 |
KDE | Cluster | 7 | 16.666667 |
Nearest Neighbor | Cluster | 1 | 2.380952 |
NKDE | LIXEL | 4 | 9.523810 |
Section split | Segments and Junctions | 11 | 26.190476 |
Spatial Correlation | Cluster | 4 | 9.523810 |
SVM | Cluster | 1 | 2.380952 |
Priorização | Freq | Perc |
---|---|---|
Density | 7 | 16.666667 |
Expected Frequencies | 7 | 16.666667 |
Features Recognition | 4 | 9.523810 |
GWR | 3 | 7.142857 |
Over Time Variations | 4 | 9.523810 |
Potential Improvement | 3 | 7.142857 |
Severity Index | 5 | 11.904762 |
Spatial Correlation | 2 | 4.761905 |
UCL | 7 | 16.666667 |
Identificação | Priorização | Freq | Perc |
---|---|---|---|
Accident Contributory Factors | Features Recognition | 1 | 2.380952 |
Analytic Hierarchy Process | Density | 1 | 2.380952 |
Bayesian Network | Severity Index | 1 | 2.380952 |
Empirical Bayes | Potential Improvement | 1 | 2.380952 |
Full-Bayesian | Expected Frequencies | 1 | 2.380952 |
Minimum Treshold Limit | Density | 1 | 2.380952 |
Minimum Treshold Limit | Potential Improvement | 1 | 2.380952 |
Minimum Treshold Limit | Severity Index | 1 | 2.380952 |
Minimum Treshold Limit | UCL | 3 | 7.142857 |
Nearest Neighbor | GWR | 1 | 2.380952 |
Nearest Neighbor | UCL | 1 | 2.380952 |
Network-Constrained | Density | 1 | 2.380952 |
Network-Constrained | Over Time Variations | 1 | 2.380952 |
Network-Constrained | Severity Index | 1 | 2.380952 |
Network-Constrained | Spatial Correlation | 2 | 4.761905 |
Probability Density Function | Expected Frequencies | 1 | 2.380952 |
Regression models | Expected Frequencies | 2 | 4.761905 |
Regression models | UCL | 1 | 2.380952 |
Semantic Segmentation | Features Recognition | 1 | 2.380952 |
Spatial Association | Density | 3 | 7.142857 |
Spatial Association | Expected Frequencies | 3 | 7.142857 |
Spatial Association | Features Recognition | 1 | 2.380952 |
Spatial Association | GWR | 2 | 4.761905 |
Spatial Association | Over Time Variations | 3 | 7.142857 |
Spatial Association | Potential Improvement | 1 | 2.380952 |
Spatial Association | Severity Index | 1 | 2.380952 |
Spatial Association | UCL | 1 | 2.380952 |
Weighted Accident Number | Density | 1 | 2.380952 |
Weighted Accident Number | Severity Index | 1 | 2.380952 |
Weighted Accident Number | UCL | 1 | 2.380952 |
XGBoost | Features Recognition | 1 | 2.380952 |
Grupamento | Unid Anal | Identificação | Priorização | Freq | Perc |
---|---|---|---|---|---|
Beta-binomial screening | Segments and Junctions | Minimum Treshold Limit | UCL | 1 | 2.380952 |
Black Spots offically | Uninformed | Semantic Segmentation | Features Recognition | 1 | 2.380952 |
Cells | Grid Cells | Minimum Treshold Limit | UCL | 1 | 2.380952 |
Cells | Grid Cells | Spatial Association | Expected Frequencies | 2 | 4.761905 |
Cells | Grid Cells | Spatial Association | Features Recognition | 1 | 2.380952 |
City Limits | Counties | Full-Bayesian | Expected Frequencies | 1 | 2.380952 |
Community Census | Block | Regression models | Expected Frequencies | 1 | 2.380952 |
Community Census | Block | Spatial Association | Expected Frequencies | 1 | 2.380952 |
Community Census | Block | Spatial Association | GWR | 2 | 4.761905 |
DBSCAN | Cluster | Weighted Accident Number | Density | 1 | 2.380952 |
Firefly Algorithm | Cluster | Minimum Treshold Limit | Density | 1 | 2.380952 |
Gaussian Mixture Models GMM | Cluster | Probability Density Function | Expected Frequencies | 1 | 2.380952 |
KDE | Cluster | Nearest Neighbor | UCL | 1 | 2.380952 |
KDE | Cluster | Network-Constrained | Spatial Correlation | 1 | 2.380952 |
KDE | Cluster | Spatial Association | Density | 2 | 4.761905 |
KDE | Cluster | Spatial Association | Potential Improvement | 1 | 2.380952 |
KDE | Cluster | Spatial Association | Severity Index | 1 | 2.380952 |
KDE | Cluster | Spatial Association | UCL | 1 | 2.380952 |
Nearest Neighbor | Cluster | Nearest Neighbor | GWR | 1 | 2.380952 |
NKDE | LIXEL | Network-Constrained | Density | 1 | 2.380952 |
NKDE | LIXEL | Network-Constrained | Over Time Variations | 1 | 2.380952 |
NKDE | LIXEL | Network-Constrained | Spatial Correlation | 1 | 2.380952 |
NKDE | LIXEL | Spatial Association | Over Time Variations | 1 | 2.380952 |
Section split | Segments and Junctions | Analytic Hierarchy Process | Density | 1 | 2.380952 |
Section split | Segments and Junctions | Bayesian Network | Severity Index | 1 | 2.380952 |
Section split | Segments and Junctions | Empirical Bayes | Potential Improvement | 1 | 2.380952 |
Section split | Segments and Junctions | Minimum Treshold Limit | Potential Improvement | 1 | 2.380952 |
Section split | Segments and Junctions | Minimum Treshold Limit | Severity Index | 1 | 2.380952 |
Section split | Segments and Junctions | Minimum Treshold Limit | UCL | 1 | 2.380952 |
Section split | Segments and Junctions | Regression models | Expected Frequencies | 1 | 2.380952 |
Section split | Segments and Junctions | Regression models | UCL | 1 | 2.380952 |
Section split | Segments and Junctions | Weighted Accident Number | Severity Index | 1 | 2.380952 |
Section split | Segments and Junctions | Weighted Accident Number | UCL | 1 | 2.380952 |
Section split | Segments and Junctions | XGBoost | Features Recognition | 1 | 2.380952 |
Spatial Correlation | Cluster | Network-Constrained | Severity Index | 1 | 2.380952 |
Spatial Correlation | Cluster | Spatial Association | Density | 1 | 2.380952 |
Spatial Correlation | Cluster | Spatial Association | Over Time Variations | 2 | 4.761905 |
SVM | Cluster | Accident Contributory Factors | Features Recognition | 1 | 2.380952 |