| 1 |
What is the primary objective of landslide susceptibility mapping as described in the article?
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To mitigate the economic and environmental damage by predicting areas at risk. |
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The primary goal of landslide susceptibility mapping is to predict areas that are at risk of landslides, which can help environmental damage caused by such events. |
I find the information in sciencedirect website that is landslide susceptibility mapping is a crucial tool in disaster risk reduction and environmental management. This research named Comparing the effectiveness of landslide susceptibility mapping by using the frequency ratio and hybrid MCDM models. |
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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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Random Forest |
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According to Landslide susceptibility estimation by random forests technique research , Random Forest showed the highest success rate in predicting landslides compared to other choices. |
I still trusted in 3W method then I find the research in google scholar then I find this reseach named Landslide susceptibility estimation by random forests technique: Sensitivity and scaling issues that shows the clear answer for this question. |
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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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12 percent is the highly susceptible zone covers of the district so the area that not highly susceptible is 100-12 = 88 percent but the question asks for the area so the answer will be 75-12 = 63 percent. |
I use 3W method so I would analyse first and then calculated but I would search for the meanong of the word such as susceptible to landslides. |
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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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If 80percent of the 255 landslides were used fortraining, then: 80/100 * 255=204 landslides used for training 80/100 *255=204 landslides used for training. The remaining 20percent would be used for testing:255−204 = 51landslides used for testing
255−204 = 51landslides used for testing |
I see this type of question in statistic topic in school so I could solve it. |
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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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Area of the very high susceptible zone = Percent/100 *Total Area of the district
therefore Area of the very high susceptible zone = 9/100 * 7,000 = 630 |
I use 3W method which I often do first I find the meaning of the area of the very high susceptible zone then I find the formula and I need to recheck in the unit very closely. |
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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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This is the formula that I found Specificity = 1 − (FPR) therefore Specificity = 1 − 0.05 = 0.95 |
I still use 3W method to search what question want and what is the formula and need to careful with unit. |
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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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Excellent |
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The area under the curve (AUC) of the receiver operating characteristic (ROC) curve is a measure of how well the model can distinguish between classes (typically positive and negative). |
I search what we need to calculated in google and then I find this research in google scholar ,Credit risk modelling and prediction:
Logistic regression versus machinelearning boosting algorithms , this tell about how to rate the model's accuracy from the information that
I have. |
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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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Percentage=( Training dataset size/Total occurrences )*100
Percentage=( 204/255 )*100 = 80 percent |
This formula I didn't search for but I use normal math to solve it. |
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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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Accuracy= 100percent − Error rate
Accuracy= 100percent − 25percent =75percent |
This question I just analyse and I think just use the normal math to solve firrst we just subtract eorror from 100 percent then we can find the answer. |
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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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181/204 * 100 = 88.72549 so the nearest answer is 88.73 percent. |
This one is the normal math and the question already give the element for calculating. |
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| 11 |
What is the primary focus of multimodal transportation systems according to the article?
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Enhancing environmental sustainability and safety. |
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Multimodal transportation systems focus on integrating various modes of transport in a way that emphasizes environmental sustainability and safety. |
I ever study about UN Sustainable Development Goals - SDGs this topic tell us about the information of this question. In this topic there have a topic which related to enhacing trasportation and safety. |
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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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According to Relevant Methodological Literature the FAHP-DEA method combines fuzzy AHP for weighting risk factors under uncertainty and DEA for optimizing route efficiency. This approach enables systematic prioritization and effective risk management in multimodal transportation systems. |
I find the answer in google scholar which name is Relevant Methodological Literature. This report is very helpful in this question for analyse Fuzzy Analytical Hierarchy Process (FAHP) and Data Envelopment Analysis (DEA). |
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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 total weight for all criteria sum to 1. The weights for operational risk and security risk are given as 0.157 and 0.073. The combined weight of the remaining three criteria is calculated as: 1−( 0.157 + 0.073 ) = 1 − 0.230 = 0.7701 − ( 0.157 + 0.073 ) = 1 − 0.230 = 0.770 |
This question I need to analyse and search for correct way to calculation so I search for all the meaning of these 3 criteria after that follow the instruction and I could easily get the answer. |
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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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R = 0.2 * 0.5 = 0.1 |
This question already give the formula so I find the meaning of individual number that this question give me so the 0.2 is P while 0.5 is C then the answer is 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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0.438 |
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Aggregate risk score = sum of weight time to local risk score
Aggregate risk score= (0.321*0.5) + (0.388*0.6) + (0.157*0.4) + (0.073*0.3) + (0.061*0.2) = 0.438 |
This question is based on the weighted scoring method, commonly used in risk management and decision-making to combine multiple criteria into a single score. |
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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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0.18 |
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R = 0.6 * 0.6 * 0.2 = 0.18 , P from 3/5 = 0.6 C from 3/5 = 0.6 and D is 20/100 |
So I already get the formula for calculation from the answer so I just need to know tghe P C D then I find tghe meaning of individual then we got the answer. |
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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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Contribution = Weight * Local risk score
Contribution = 0.061 * 0.4 = 0.0244 |
So I just searching for the formula for calcutaing and I found that I got the element for calculation already. |
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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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New infrastructure risk contribution: 0.400 * 0.2 = 0.080 |
This question are similar to pass question I could assume that the change in overall risk score comes from updating the infrastructure risk contribution, and the result is 0.080. |
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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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Initial contribution: 0.073 * 0.4 = 0.0292
New contribution: 0.073 * 0.35 = 0.02555
Change in contribution: 0.0292 − 0.02555 = 0.00365 |
From my styudy , the change is calculated by updating the contribution based on the new risk score, which is lower than the original score. |
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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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0.14647 |
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Freight-damage risk contribution: 0.1 * 0.321 = 0.0321
Infrastructure risk contribution: 0.2 * 0.388 = 0.0776
Operational risk contribution: 0.15 * 0.157 = 0.02355 Therefore the total contribution = 0.0321 + 0.0776 + 0.02355 = 0.14647 |
So this one is weighted scoring method similar to a lot of pass answer. |
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