| 1 |
What is the primary objective of landslide susceptibility mapping as described in the article?
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To map the geological features of Bangladesh without practical application. |
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By mapping out the areas in Bangladesh, the high potential areas of landslide can be identified. |
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| 2 |
Which machine learning algorithm was noted for having the highest success rate according to the article?
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Decision and Regression Tree |
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DRT is the most realistic model |
This information was retrieved by a research that aimed to prepare and evaluate landslide susceptibility maps. |
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| 3 |
If the area of Chattogram district is 75% susceptible to landslides, and the highly susceptible zone covers approximately 12% of the district, what is the area (in percentage) that is not highly susceptible?
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63% |
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The nit highly susceptible zone covers around 63% |
75%-12% |
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| 4 |
Considering that the total number of analyzed landslides is 255, and 80% were used for training the models, how many landslide instances were used for testing?
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51 |
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51 instances were used for testing |
80%=training therefore: 20%=testing
20% x 255= 51 |
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| 5 |
If the total area of Chattogram district is 7,000 km² and the very high susceptible zone covers 9% of the district, what is the area of the very high susceptible zone in km²?
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630 km² |
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In km^3 the area of the highly susceptible zone is 630 |
(90/100) x 7000 |
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| 6 |
Assuming the false positive rate (FPR) for the logistic regression model is 0.05 and the true positive rate (TPR) is 0.95, calculate the specificity of the model.
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0.95 |
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The specificity is 0.95 |
Specificity = TN/TN+FP
TN = 0.95 (1-0.05)
Therefore: 0.95/(0.95+0.05) =0.95 |
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| 7 |
Given that the area under the ROC curve (AUC) for the logistic regression model is 0.963, and the prediction rate is measured as the area under this curve, rate the model's prediction accuracy.
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Average |
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| 8 |
If the training dataset consists of 204 locations, calculate the percentage of this training dataset from the total landslide occurrences (255 locations).
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80% |
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The percentage of this training data set from the total landslide occurrences is 80% |
(204/255) x100 |
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| 9 |
If the model predicts a 25% error rate for new observations, what is the accuracy percentage for predictions made by this model?
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75% |
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The accuracy percentage prediction made by the model is 75% |
100%-25%=75% |
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| 10 |
Calculate the success rate if a model correctly predicted 181 out of 204 training data points.
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88.73% |
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The success rate is approximately 88.73% |
(181/204)x100 |
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| 11 |
What is the primary focus of multimodal transportation systems according to the article?
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Reducing costs irrespective of environmental impact. |
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| 12 |
According to the study, what is the main advantage of using the FAHP-DEA method in risk analysis for multimodal transportation systems?
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It allows for precise risk prioritization and optimization of routes. |
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The FAHP method is used to weight each criteria out while the DEA method is use to generate the local risk scores. |
This method is proposed to overcome difficulties proven by a study. |
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| 13 |
If the risk analysis model has five criteria and assigns importance weights such that the total sums up to 1, and the weights for operational risk and security risk are 0.157 and 0.073 respectively, what is the combined weight of the remaining three criteria?
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0.770 |
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The combined weight of the remaining criteria is 0.77 |
1-0.157-0.073=0.77 |
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| 14 |
If the probability of an accident occurring on a route is 0.2 and the consequence severity is rated at 0.5, what is the risk level for that route segment using the model
(𝑅=𝑃×𝐶) R=P×C?
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0.1 |
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The risks level is 0.1 |
0.5 x 0.2 =0.1 |
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| 15 |
Calculate the aggregate risk score if the weights of the criteria are 0.321, 0.388, 0.157, 0.073, and 0.061, and the local risk scores for a route are 0.5, 0.6, 0.4, 0.3, and 0.2 respectively.
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| 16 |
If the probability assessment for a risk is ranked 3 on a scale of 5 and the severity assessment is also ranked 3, with the transport segment accounting for 20% of the total route distance, calculate the risk assessment using the formula (𝑅=𝑃×𝐶×𝐷) R=P×C×D?
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| 17 |
Given that the weight for environmental risk is 0.061 and the local risk score for a route is 0.4, calculate the contribution of environmental risk to the overall risk score.
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0.0244 |
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The contribution of environmental risk is 0.0244 |
0.4x0.061 |
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| 18 |
Calculate the new overall risk score if the weight of infrastructure risk is increased from 0.388 to 0.400 while keeping other parameters constant, given that its local risk score is 0.2.
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0.080 |
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The new overall score would be 0.08 |
0.4x0.2 |
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| 19 |
If a mode of transportation has a risk weight of 0.073 and its risk score is reassessed from 0.4 to 0.35, what is the change in its contribution to the overall risk score?
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0.00365 |
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The change would be 0.00365 |
0.4-0.35=0.05
0.05 x 0.073 =0.00365 |
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| 20 |
If the local weights of freight-damage risk, infrastructure risk, and operational risk are 0.1, 0.2, and 0.15 respectively, what is their total contribution to the risk score if their respective weights are 0.321, 0.388, and 0.157?
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