The mechanical parameters of materials in a dam body and dam foundation tend to change when dams are reinforced in aging processes.It is important to use an early-warning index to reflect the safety status of dams,par...The mechanical parameters of materials in a dam body and dam foundation tend to change when dams are reinforced in aging processes.It is important to use an early-warning index to reflect the safety status of dams,particularly of heightened projects in the impoundment period.Herein,a new method for monitoring the safety status of heightened dams is proposed based on the deformation monitoring data of a dam structure,a statistical model,and finite-element numerical simulation.First,a fast optimization inversion method for estimation of dam mechanical parameters was developed,which used the water pressure component extracted from a statistical model,an improved inversion objective function,and a genetic optimization iterative algorithm.Then,a finite element model of a heightened concrete gravity dam was established,and the deformation behavior of the dam with rising water levels in the impoundment period was simulated.Subsequently,mechanical parameters of aged dam parts were calculated using the fast optimization inversion method with simulated deformation and the water pressure deformation component obtained by the statistical model under the same conditions of water pressure change.Finally,a new earlywarning index of dam deformation was constructed by means of the forward-simulated deformation and other components of the statistical model.The early-warning index is useful for forecasting dam deformation under different water levels,especially high water levels.展开更多
The period economic fluctuation is vital for an enterprise to exist and further develop, it directly affect the enterprise financial health. So, it is significant to build up financial early-warning index and measure ...The period economic fluctuation is vital for an enterprise to exist and further develop, it directly affect the enterprise financial health. So, it is significant to build up financial early-warning index and measure the warning condition that the enterprise faces and take the effective measures to eliminate. We criticize Altman’sZ calculating model and build up some new indexes for enterprise financial early-warning condition measuring and making sound decision.展开更多
This paper estimates and decomposes the output-oriented three-stage cost Malmquist productivity index of the Taiwan Residents biotech and biopharmaceutical （B＆BP） industry in 2004-2007 periods. The empirical estima...This paper estimates and decomposes the output-oriented three-stage cost Malmquist productivity index of the Taiwan Residents biotech and biopharmaceutical （B＆BP） industry in 2004-2007 periods. The empirical estimations proceed in three stages. Following the methodology of Yang and Huang （2009） with the assumption of variable return to scale （VRS） in the first stage, the original cost Malmquist productivity index （CM） is decomposed into five sources of productivity change： pure technical efficiency change, technical change, allocative efficiency change （AEC）, input-price effect, and cost scale efficiency change. The method of Yang and Huang （2009） is an excellent contribution, but it did not deal with the exogenous environmental variables and noises. In the second stage, the original input variables are adjusted by the exogenous environmental variables. Finally, adjusted input variables produced by the second stage are reused for obtaining the reality of CM in the third stage.展开更多
基金This work was supported by the National Key Research and Development Program of China(Grant No.2018YFC0407104)the National Natural Science Foundation of China(Grants No.52079049 and 51739003)+1 种基金the Central University Basic Research Project(Grant No.B200202160)the Water Science Project of Xinjiang(Grant No.YF 2020-05).
文摘The mechanical parameters of materials in a dam body and dam foundation tend to change when dams are reinforced in aging processes.It is important to use an early-warning index to reflect the safety status of dams,particularly of heightened projects in the impoundment period.Herein,a new method for monitoring the safety status of heightened dams is proposed based on the deformation monitoring data of a dam structure,a statistical model,and finite-element numerical simulation.First,a fast optimization inversion method for estimation of dam mechanical parameters was developed,which used the water pressure component extracted from a statistical model,an improved inversion objective function,and a genetic optimization iterative algorithm.Then,a finite element model of a heightened concrete gravity dam was established,and the deformation behavior of the dam with rising water levels in the impoundment period was simulated.Subsequently,mechanical parameters of aged dam parts were calculated using the fast optimization inversion method with simulated deformation and the water pressure deformation component obtained by the statistical model under the same conditions of water pressure change.Finally,a new earlywarning index of dam deformation was constructed by means of the forward-simulated deformation and other components of the statistical model.The early-warning index is useful for forecasting dam deformation under different water levels,especially high water levels.
文摘The period economic fluctuation is vital for an enterprise to exist and further develop, it directly affect the enterprise financial health. So, it is significant to build up financial early-warning index and measure the warning condition that the enterprise faces and take the effective measures to eliminate. We criticize Altman’sZ calculating model and build up some new indexes for enterprise financial early-warning condition measuring and making sound decision.
文摘This paper estimates and decomposes the output-oriented three-stage cost Malmquist productivity index of the Taiwan Residents biotech and biopharmaceutical （B＆BP） industry in 2004-2007 periods. The empirical estimations proceed in three stages. Following the methodology of Yang and Huang （2009） with the assumption of variable return to scale （VRS） in the first stage, the original cost Malmquist productivity index （CM） is decomposed into five sources of productivity change： pure technical efficiency change, technical change, allocative efficiency change （AEC）, input-price effect, and cost scale efficiency change. The method of Yang and Huang （2009） is an excellent contribution, but it did not deal with the exogenous environmental variables and noises. In the second stage, the original input variables are adjusted by the exogenous environmental variables. Finally, adjusted input variables produced by the second stage are reused for obtaining the reality of CM in the third stage.
