Economic Risk Assessment of Future Debris Flows by Machine Learning Method

A reliable economic risk map is critical for effective debris-flow mitigation.However,the uncertainties surrounding future scenarios in debris-flow frequency and magnitude restrict its application.To estimate the economic risks caused by future debris flows,a machine learning-based method was proposed to generate an economic risk map by multiplying a debris-flow hazard map and an economic vulnerability map.We selected the Gyirong Zangbo Basin as the study area because frequent severe debris flows impact the area every year.The debris-flow hazard map was developed through the multiplication of the annual probability of spatial impact,temporal probability,and annual susceptibility.We employed a hybrid machine learning model-certainty factor-genetic algorithm-support vector classification-to calculate susceptibilities.Simultaneously,a Poisson model was applied for temporal probabilities,while the determination of annual probability of spatial impact relied on statistical results.Additionally,four major elements at risk were selected for the generation of an economic loss map:roads,vegetation-covered land,residential buildings,and farmland.The economic loss of elements at risk was calculated based on physical vulnerabilities and their economic values.Therefore,we proposed a physical vulnerability matrix for residential buildings,factoring in impact pressure on buildings and their horizontal distance and vertical distance to debrisflow channels.In this context,an ensemble model(XGBoost) was used to predict debris-flow volumes to calculate impact pressures on buildings.The results show that residential buildings occupy 76.7% of the total economic risk,while roadcovered areas contribute approximately 6.85%.Vegetation-covered land and farmland collectively represent 16.45% of the entire risk.These findings can provide a scientific support for the effective mitigation of future debris flows.

Risk assessment of transnational oil investment in Central Asia using a fuzzy comprehensive evaluation method

Central Asia(including five countries:Kazakhstan,Kyrgyzstan,Turkmenistan,Uzbekistan,and Tajikistan)is rich in oil reserves and has become one of the most important target regions for global oil investment.The construction of the Silk Road Economic Belt has prompted Central Asia to look outwards for more collaborations in the oil industry.China's need for oil investment in Central Asia has also increased significantly.This research established a comprehensive index system for assessing the risks of transnational oil investment in Central Asia.The system incorporated political,regulatory,economic,social,and infrastructural indices.Based on the Delphi method and fuzzy comprehension evaluation method,we qualitatively and quantitatively assessed and analyzed the risks of transnational oil investment in Central Asia.The results indicate that the risk score for regulatory risk was highest with the value of 6.1670,indicating a high risk level in transnational oil investment,followed by economic,social,political,and infrastructural risk indices.Of the 18 secondary risk indices calculated,there were seven indices with the probability of high risk occurrence exceeded 30.0%and the descending order was as follows:establishment of mining rights;host country intervention in operations;taxing system;stability of regulations;war and turmoil;labor capital;and ethnic,cultural,and religious differences.These seven critical risks should be watched closely and avoided during transnational oil investment in Central Asia.This study provides a comprehensive understanding of the potential risks of investing oil in Central Asia.The findings demonstrate the causes of these risks and provide a scientific basis for reasonably avoiding oil investment risk and improving investment benefits for both host and investing countries.

The "Stagflation" Risk and Policy Control: Causes, Governance and Inspirations

The blend of economic stagnation and inflation is a challenge to the contemporary macroeconomic study.The causes,influence and policy implications of"stagflation"have been academically controversial.This paper starts with the connections between energy crises and stagflation to research the causes of"stagflation"in the 1970s and analyze the realistic impact of energy crises.It then comparatively studies the current economic landscape and the landscape in the 1970s for similarities and differences,digs into the origin of the current macroeconomic situation,and on such basis proposes policy suggestions.

Risk Governance,Assessment,and Economic Impacts

Due to climate change,growing urbanization,and population migration the social and economic impacts of natural hazards have been increasing worldwide.The challenge for risk science,both methodologically and conceptually,is to integrate robust multi-hazard evaluation models with