Accurate displacement prediction is critical for the early warning of landslides.The complexity of the coupling relationship between multiple influencing factors and displacement makes the accurate prediction of displ...Accurate displacement prediction is critical for the early warning of landslides.The complexity of the coupling relationship between multiple influencing factors and displacement makes the accurate prediction of displacement difficult.Moreover,in engineering practice,insufficient monitoring data limit the performance of prediction models.To alleviate this problem,a displacement prediction method based on multisource domain transfer learning,which helps accurately predict data in the target domain through the knowledge of one or more source domains,is proposed.First,an optimized variational mode decomposition model based on the minimum sample entropy is used to decompose the cumulative displacement into the trend,periodic,and stochastic components.The trend component is predicted by an autoregressive model,and the periodic component is predicted by the long short-term memory.For the stochastic component,because it is affected by uncertainties,it is predicted by a combination of a Wasserstein generative adversarial network and multisource domain transfer learning for improved prediction accuracy.Considering a real mine slope as a case study,the proposed prediction method was validated.Therefore,this study provides new insights that can be applied to scenarios lacking sample data.展开更多
The ecological costs of open pit metal mining are quantified, which include lost value of direct eco-services, lost value of indirect eco-services, prevention and restoration costs, and cost of carbon emission from en...The ecological costs of open pit metal mining are quantified, which include lost value of direct eco-services, lost value of indirect eco-services, prevention and restoration costs, and cost of carbon emission from energy consumption. These ecological costs are incorporated in an iterative ultimate pit optimization algorithm. A case study is presented to demonstrate the influence of ecological costs on pit design outcome. The results show that it is possible to internalize ecological costs in mine designs. The pit optimization outcome shifts considerably to the conservative side and the profitability decreases substantially when ecological costs are accounted for.展开更多
Chengdu City is in the period of rapid urbanization and industrialization, and the disturbance derived from human activities on environment is increasing remarkablely in recent 20 years. The pressure on environment, e...Chengdu City is in the period of rapid urbanization and industrialization, and the disturbance derived from human activities on environment is increasing remarkablely in recent 20 years. The pressure on environment, economy and population is also increasing and land use in Chengdu has changed enormously. As struc- ture and function of land ecological system change obviously, sustainable development of land productivity has been an important goal and strategic task from now on, and it is necessary to systematically research land ecological carrying capacity based on ecological footprint. The ecological footprint of Chengdu City in the past ten years was calculated and analyzed from the spatial and temporal aspects according to statistical data from 1998 to 2008, as per ecological footprint method, ecological carrying capacity and the GIS spatial analysis method, and regression analysis method. The ecological footprint and ecological carrying capacity values from 2009 to 2019 in Chengdu City were predicted through calculation results in the past ten years. The results show that the ecological footprint and ecological deficit of land use from 1998 to 2008 increased in Chengdu City. The ecological deficit of land use within the city center was in high levels in the past ten years, and the ecological footprint kept raising, especially in areas, such as Shuangliu, Chongzhou, Qingyang among 9 city areas, 4 counties and 6 districts in Chengdu City. There is fanlike distribution of ecological deficit of land use. Analysis shows that the social and natural ecological system is uneven distribution, which is not in sustainable de- velopment situation. The results of the study show that the economic, social and natural ecological system in Chengdu City is not sustainable, and the ecological foot- print is uneven distribution. The analysis of the dynamic change of land ecological carrying capacity in Chengdu City is very important for city government in the pro- cess of the vigorous development in new Tianfu Xinqu, and redevelopment in the northern part of this city.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.51674169)Department of Education of Hebei Province of China(Grant No.ZD2019140)+1 种基金Natural Science Foundation of Hebei Province of China(Grant No.F2019210243)S&T Program of Hebei(Grant No.22375413D)School of Electrical and Electronics Engineering。
文摘Accurate displacement prediction is critical for the early warning of landslides.The complexity of the coupling relationship between multiple influencing factors and displacement makes the accurate prediction of displacement difficult.Moreover,in engineering practice,insufficient monitoring data limit the performance of prediction models.To alleviate this problem,a displacement prediction method based on multisource domain transfer learning,which helps accurately predict data in the target domain through the knowledge of one or more source domains,is proposed.First,an optimized variational mode decomposition model based on the minimum sample entropy is used to decompose the cumulative displacement into the trend,periodic,and stochastic components.The trend component is predicted by an autoregressive model,and the periodic component is predicted by the long short-term memory.For the stochastic component,because it is affected by uncertainties,it is predicted by a combination of a Wasserstein generative adversarial network and multisource domain transfer learning for improved prediction accuracy.Considering a real mine slope as a case study,the proposed prediction method was validated.Therefore,this study provides new insights that can be applied to scenarios lacking sample data.
基金Project(50974041)supported by the National Natural Science Foundation of ChinaProject(NCET-11-0073)supported by Program for New Century Excellent Talents in University of Ministry of Education of China+1 种基金Project(201102065)supported by the Natural Science Foundation of Liaoning Province,ChinaProject(2012921075)supported by the Ten Million Talent Project of Liaoning Province,China
文摘The ecological costs of open pit metal mining are quantified, which include lost value of direct eco-services, lost value of indirect eco-services, prevention and restoration costs, and cost of carbon emission from energy consumption. These ecological costs are incorporated in an iterative ultimate pit optimization algorithm. A case study is presented to demonstrate the influence of ecological costs on pit design outcome. The results show that it is possible to internalize ecological costs in mine designs. The pit optimization outcome shifts considerably to the conservative side and the profitability decreases substantially when ecological costs are accounted for.
基金Supported by National High-tech R&D Program of China(863Program)(2009AA12Z-140)National Natural Science Foundation of China(40771144,40575035)Scientific Research Foundation of Sichuan Normal University(SXK11002)~~
文摘Chengdu City is in the period of rapid urbanization and industrialization, and the disturbance derived from human activities on environment is increasing remarkablely in recent 20 years. The pressure on environment, economy and population is also increasing and land use in Chengdu has changed enormously. As struc- ture and function of land ecological system change obviously, sustainable development of land productivity has been an important goal and strategic task from now on, and it is necessary to systematically research land ecological carrying capacity based on ecological footprint. The ecological footprint of Chengdu City in the past ten years was calculated and analyzed from the spatial and temporal aspects according to statistical data from 1998 to 2008, as per ecological footprint method, ecological carrying capacity and the GIS spatial analysis method, and regression analysis method. The ecological footprint and ecological carrying capacity values from 2009 to 2019 in Chengdu City were predicted through calculation results in the past ten years. The results show that the ecological footprint and ecological deficit of land use from 1998 to 2008 increased in Chengdu City. The ecological deficit of land use within the city center was in high levels in the past ten years, and the ecological footprint kept raising, especially in areas, such as Shuangliu, Chongzhou, Qingyang among 9 city areas, 4 counties and 6 districts in Chengdu City. There is fanlike distribution of ecological deficit of land use. Analysis shows that the social and natural ecological system is uneven distribution, which is not in sustainable de- velopment situation. The results of the study show that the economic, social and natural ecological system in Chengdu City is not sustainable, and the ecological foot- print is uneven distribution. The analysis of the dynamic change of land ecological carrying capacity in Chengdu City is very important for city government in the pro- cess of the vigorous development in new Tianfu Xinqu, and redevelopment in the northern part of this city.
