| 1 |
What is the purpose of the empirical case study on coal manufacturing in the paper?
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To demonstrate the proposed decision support model |
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บทความ : Multi-objective Optimization of Freight Route Choices in Multimodal Transportation | Atlantis Press (atlantis-press.com) |
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| 2 |
Which factor does the model NOT consider in route selection for a multimodal transportation network?
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Cultural preferences |
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บทความ : Multi-objective Optimization of Freight Route Choices in Multimodal Transportation | Atlantis Press (atlantis-press.com) |
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| 3 |
What is the role of expert judgments in the decision support model?
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They influence the weights obtained from AHP |
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the ZOGP's objective function to allow selecting highest AHP weights of the alternatives depends on the resource |
บทความ : Multi-objective Optimization of Freight Route Choices in Multimodal Transportation | Atlantis Press (atlantis-press.com) |
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| 4 |
What logistics system aspect does the proposed methodology aim to improve?
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Cost management |
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In logistics, factors affecting customer satisfaction include delivery time, cost, packaging, and communication. |
บทความ : Multi-objective Optimization of Freight Route Choices in Multimodal Transportation | Atlantis Press (atlantis-press.com) |
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| 5 |
Essay | Describe the role of Analytic Hierarchy Process (AHP) and Zero-One Goal Programming (ZOGP) in the decision support model for determining an optimal multimodal transportation route. Explain how these methodologies contribute to the model's effectiveness and discuss any potential limitations.
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This paper develops a decision support model using an analytic hierarchy process (AHP) and zero-one goal programing (ZOGP). This proposed approach is applied to a real-world problem to enable the selection of the best route for transporting goods from the anchorage area in the Gulf. By integrating multiple modes of transport such as rail, road, water, and air, companies can leverage the strengths of each mode to optimize the movement of goods. Increased Flexibility: Multimodal transportation provides supply chain businesses with greater flexibility in managing their logistics operations. |
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บทความ : Multi-objective Optimization of Freight Route Choices in Multimodal Transportation | Atlantis Press (atlantis-press.com) |
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| 6 |
What is the role of the FAHP method in the proposed risk analysis model?
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To determine the weights of each risk criterion |
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The proposed FAHP-DEA methodology uses the FAHP method to determine the weights of each risk criterion. |
บทความ : A Risk Analysis Based on a Two-Stage Model of Fuzzy AHP-DEA for Multimodal Freight Transportation Systems | IEEE Journals & Magazine | IEEE Xplore |
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| 7 |
Which industry is used as a case study in the proposed risk analysis model?
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Coal |
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A case study of the coal industry demonstrates that the proposed risk analysis model is practical and allows users to more . |
บทความ : A Risk Analysis Based on a Two-Stage Model of Fuzzy AHP-DEA for Multimodal Freight Transportation Systems | IEEE Journals & Magazine | IEEE Xplore |
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| 8 |
What does the DEA method do in the proposed FAHP-DEA methodology?
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Evaluates linguistic variables and generates risk scores |
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The DEA method is employed to evaluate the linguistic variables and generate the risk scores. The simple additive |
บทความ : A Risk Analysis Based on a Two-Stage Model of Fuzzy AHP-DEA for Multimodal Freight Transportation Systems | IEEE Journals & Magazine | IEEE Xplore |
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| 9 |
Which method is used to aggregate risk scores into an overall risk score in the proposed model?
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Simple Additive Weighting (SAW) |
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The simple additive weighting (SAW) method is used to aggregate risk scores under different risk criteria into an overall risk score. |
บทความ : A Risk Analysis Based on a Two-Stage Model of Fuzzy AHP-DEA for Multimodal Freight Transportation Systems | IEEE Journals & Magazine | IEEE Xplore |
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| 10 |
Essay | Using the coal industry case study, please explain how the proposed risk analysis model is practical and aids in prioritizing risks. Discuss how this model can be beneficial for industries in optimizing multimodal transportation routes under risk decision criteria.
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Multimodal is a transportation term. Multimodal transportation includes public transportation, rail and waterways, bicycle and pedestrian. Multimodal access supports the needs of all users whether they choose to walk, bike, use transit or drive. It means more connections and more choices. One of the main risks of using a multi-modal transportation strategy is the coordination of different transport modes, operators, and regulations. Each mode of transport has its own characteristics, requirements, and standards, which can create complexity and inconsistency in the logistics processes. A case study of the coal industry demonstrates that the proposed risk analysis model is practical and allows users to more. |
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บทความ : A Risk Analysis Based on a Two-Stage Model of Fuzzy AHP-DEA for Multimodal Freight Transportation Systems | IEEE Journals & Magazine | IEEE Xplore |
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| 11 |
How were geotechnical parameters of soils at landslide-prone sites evaluated in the study?
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Satellite remote sensing datasets |
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บทความ : ARIMA and SPSS statistics based assessment of landslide occurrence in western Himalayas – ScienceDirect |
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| 12 |
What modeling techniques were used to assess the probability of landslide occurrence in the future?
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Autoregressive Moving Average (ARIMA) model |
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the probability of occurrence of landslide events in the future using Autoregressive Moving Average (ARIMA) model and IBM SPSS |
บทความ : ARIMA and SPSS statistics based assessment of landslide occurrence in western Himalayas – ScienceDirect |
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| 13 |
What is the potential application of the study's findings in hazard management?
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Devising countermeasures for managing landslides |
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This work shall help devise countermeasures for managing the landslides in the study area locally and shall serve as the guiding |
บทความ : ARIMA and SPSS statistics based assessment of landslide occurrence in western Himalayas – ScienceDirect |
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| 14 |
How does the study aim to contribute to hazard management in the Himalayas?
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By serving as a guiding framework for using artificial intelligence and machine learning |
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บทความ : ARIMA and SPSS statistics based assessment of landslide occurrence in western Himalayas – ScienceDirect |
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| 15 |
Essay | Explain the methodology employed in the study to evaluate geotechnical parameters and assess the probability of future landslide events. Discuss the potential implications of using artificial intelligence and machine learning in hazard management in the Himalayas, with reference to the study's guiding framework.
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This work shall help devise countermeasures for managing the landslides in the study area locally and shall serve as the guiding . There are also various direct methods of preventing landslides; these include modifying slope geometry, using chemical agents to reinforce slope material, installing structures such as piles and retaining walls, grouting rock joints and fissures, diverting debris pathways, and rerouting surface and underwater drainage. Hazard mapping can be done to identify the areas which are more prone to landslides. Restriction on the construction in the risky areas should be imposed. Afforestation programs should take place. Restricting development in landslide areas and protecting the existing ones. |
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บทความ : ARIMA and SPSS statistics based assessment of landslide occurrence in western Himalayas – ScienceDirect |
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| 16 |
How was the landslide inventory database divided for training and testing in the research?
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80% training, 20% testing |
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บทความ : GIS-based landslide susceptibility mapping using logistic regression, random forest and decision and regression tree models in Chattogram District, Bangladesh – ScienceDirect |
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| 17 |
Which machine learning model showed the highest prediction rate among LR, RF, and DRT?
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Logistic Regression (LR) |
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Among the models, LR showed the highest prediction rate. |
บทความ : GIS-based landslide susceptibility mapping using logistic regression, random forest and decision and regression tree models in Chattogram District, Bangladesh – ScienceDirect |
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| 18 |
What do the ROC values for training and testing data signify in the context of landslide susceptibility mapping?
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The extent of the study area |
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ROC curve is only an indicator of the general reliability of geographical prediction maps |
บทความ : GIS-based landslide susceptibility mapping using logistic regression, random forest and decision and regression tree models in Chattogram District, Bangladesh – ScienceDirect |
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| 19 |
Which model is considered more realistic according to susceptibility zones in the research?
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Decision and Regression Tree (DRT) |
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DRT is the more realistic model followed by LR. |
บทความ : GIS-based landslide susceptibility mapping using logistic regression, random forest and decision and regression tree models in Chattogram District, Bangladesh – ScienceDirect |
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| 20 |
Essay | Compare and contrast the performance of Logistic Regression (LR), Random Forest (RF), and Decision and Regression Tree (DRT) models in landslide susceptibility mapping. Discuss the strengths and limitations of each model based on the research findings.
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Overall, all three models exhibit reasonably good performances. Among the models, LR showed the highest prediction rate and DRT showed the highest success rate. According to susceptibility zones, DRT is the more realistic model followed by LR. The maps can be applied at the local scale for landslide hazard management. |
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บทความ : GIS-based landslide susceptibility mapping using logistic regression, random forest and decision and regression tree models in Chattogram District, Bangladesh – ScienceDirect |
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