To quantify unmanned aerial vehicle(UAV)flight risks in low-altitude airspace,we analyze the factors of UAV flight risks from three aspects:flight conflict,flight environment,and traffic characteristics.The aerial ris...To quantify unmanned aerial vehicle(UAV)flight risks in low-altitude airspace,we analyze the factors of UAV flight risks from three aspects:flight conflict,flight environment,and traffic characteristics.The aerial risk index and ground risk index of the UAV are constructed,the index screening model and the UAV flight risk assessment model are established,and a UAV flight risk assessment model based on K-means clustering has been proposed.Meanwhile,numerical simulations show the proposed method can not only evaluate the UAV flight risks effectively,but also provide technical support for UAV risk management and control.展开更多
Different models have been proposed in corporate finance literature for predicting the risk of firm＇s bankruptcy and insolvency. In spite of the large amount of empirical findings, significant issues are still unsolv...Different models have been proposed in corporate finance literature for predicting the risk of firm＇s bankruptcy and insolvency. In spite of the large amount of empirical findings, significant issues are still unsolved. In this paper, the authors developed dynamic statistical models for bankruptcy prediction of Italian firms in the industrial sector by using financial indicators. The model specification has been obtained via different variable selection techniques, and the predictive accuracy of the proposed default risk models has been evaluated at various horizons by means of different accuracy measures. The reached results give evidence that dynamic models have a better performance in any of the considered scenarios.展开更多
Environmental risks pertaining to contaminated soils have been well studied,while little attention has been paid to the risks of the soils after remediation. In this study,a concept model developed based on fuzzy set ...Environmental risks pertaining to contaminated soils have been well studied,while little attention has been paid to the risks of the soils after remediation. In this study,a concept model developed based on fuzzy set theory was applied to evaluate the uncertainties of three risk indicators,namely,plant growth,groundwater safety and human health,of a restored site that had been previously polluted by heavy metals. The concept model classified the grade and importance of risk factors by an 11-level ranking system and was able to yield a comprehensive risk result rather than multi-risk results for complex risk indicators. Modeling results showed that the risks to the three indicators were effectively reduced after the remediation. Moreover,great sensitivity of the risks was found related to the weight distribution among the three risk indicators. In general,the risks of both polluted and restored soils to the environment were in the order of groundwater safety > plant growth > human health. The model was proved to solve the problems of multi-risk results due to complex risk indicators that previously encountered by other researchers,which made it helpful in decision-making and management of restored soils.展开更多
基金supported in part by the National Natural Science Foundation of China (Nos. 71971114,61573181)Open Grant of State Key Laboratory of Air Traffic Management System and Technique(No. SKLATM201801).
文摘To quantify unmanned aerial vehicle(UAV)flight risks in low-altitude airspace,we analyze the factors of UAV flight risks from three aspects:flight conflict,flight environment,and traffic characteristics.The aerial risk index and ground risk index of the UAV are constructed,the index screening model and the UAV flight risk assessment model are established,and a UAV flight risk assessment model based on K-means clustering has been proposed.Meanwhile,numerical simulations show the proposed method can not only evaluate the UAV flight risks effectively,but also provide technical support for UAV risk management and control.
文摘Different models have been proposed in corporate finance literature for predicting the risk of firm＇s bankruptcy and insolvency. In spite of the large amount of empirical findings, significant issues are still unsolved. In this paper, the authors developed dynamic statistical models for bankruptcy prediction of Italian firms in the industrial sector by using financial indicators. The model specification has been obtained via different variable selection techniques, and the predictive accuracy of the proposed default risk models has been evaluated at various horizons by means of different accuracy measures. The reached results give evidence that dynamic models have a better performance in any of the considered scenarios.
基金Supported by the National Natural Science Foundation of China(Nos.41171374 and 41101483)the Fundamental Research Funds for the Central Universities of China(No.101gzd10)+1 种基金the National Science Foundation for Distinguished Young Scholars of China(No.41225004)the National High Technology Research and Development Program of China(No.2012-AA-06A202)
文摘Environmental risks pertaining to contaminated soils have been well studied,while little attention has been paid to the risks of the soils after remediation. In this study,a concept model developed based on fuzzy set theory was applied to evaluate the uncertainties of three risk indicators,namely,plant growth,groundwater safety and human health,of a restored site that had been previously polluted by heavy metals. The concept model classified the grade and importance of risk factors by an 11-level ranking system and was able to yield a comprehensive risk result rather than multi-risk results for complex risk indicators. Modeling results showed that the risks to the three indicators were effectively reduced after the remediation. Moreover,great sensitivity of the risks was found related to the weight distribution among the three risk indicators. In general,the risks of both polluted and restored soils to the environment were in the order of groundwater safety > plant growth > human health. The model was proved to solve the problems of multi-risk results due to complex risk indicators that previously encountered by other researchers,which made it helpful in decision-making and management of restored soils.
