This study combines the analytical model to build a landside monitoring decision support system of the Web GIS. The landslide area of Lishan is a case study for the research. The analysis of the risk degree for the la...This study combines the analytical model to build a landside monitoring decision support system of the Web GIS. The landslide area of Lishan is a case study for the research. The analysis of the risk degree for the landslide area in Lishan is based on the three-layer architecture of Fuzzy Analytic Hierarchical Process （FAHP）. There are four fuzzy model structures used in monitoring devices： rainfall, groundwater level, Time Domain Reflectometry （TDR） monitored the subsurface deformation, and Global Positioning System （GPS） monitored ground displacement. These structures are relative to four membership functions that are used to classify four states, including safety, attention, warning, and danger. The risk degree of the landslide area can be obtained through the fuzzy rules by determining management criteria. Calculating the total scores of historical monitoring record of the rainfall, groundwater level, TDR, and GPS through the fuzzy theory can determine the analytical results of risk degrees in Lishan landslide area. In this whole area, management criterion is in the state of attention when the total score is larger than 72, in the state of warning when total score is larger than 95, and in the state of danger when total score is larger than 113. The system provides real-time monitoring data, and prewarning decision support in order to announce and prevent the disaster at the earliest time.展开更多
Financial early-warning is the main content of corporate financial manage- ment. This paper discusses the forecasting methods of corporate financial early-warning system, and its role in enterprise financial crisis pr...Financial early-warning is the main content of corporate financial manage- ment. This paper discusses the forecasting methods of corporate financial early-warning system, and its role in enterprise financial crisis prevention. With analyzing cases to illus- trate the application of financial early-warning system in Chinese enterprises.展开更多
文摘This study combines the analytical model to build a landside monitoring decision support system of the Web GIS. The landslide area of Lishan is a case study for the research. The analysis of the risk degree for the landslide area in Lishan is based on the three-layer architecture of Fuzzy Analytic Hierarchical Process （FAHP）. There are four fuzzy model structures used in monitoring devices： rainfall, groundwater level, Time Domain Reflectometry （TDR） monitored the subsurface deformation, and Global Positioning System （GPS） monitored ground displacement. These structures are relative to four membership functions that are used to classify four states, including safety, attention, warning, and danger. The risk degree of the landslide area can be obtained through the fuzzy rules by determining management criteria. Calculating the total scores of historical monitoring record of the rainfall, groundwater level, TDR, and GPS through the fuzzy theory can determine the analytical results of risk degrees in Lishan landslide area. In this whole area, management criterion is in the state of attention when the total score is larger than 72, in the state of warning when total score is larger than 95, and in the state of danger when total score is larger than 113. The system provides real-time monitoring data, and prewarning decision support in order to announce and prevent the disaster at the earliest time.
文摘Financial early-warning is the main content of corporate financial manage- ment. This paper discusses the forecasting methods of corporate financial early-warning system, and its role in enterprise financial crisis prevention. With analyzing cases to illus- trate the application of financial early-warning system in Chinese enterprises.
