The gray renewal GM (1,1) landslide prediction model was established by improving the gray model. Based on the established model, the author has made prediction of landslide deformation to the Xiangjiapo landslide and...The gray renewal GM (1,1) landslide prediction model was established by improving the gray model. Based on the established model, the author has made prediction of landslide deformation to the Xiangjiapo landslide and the Lianziya dangerous rock body. The results show that the gray renewal GM (1,1) model can supplement the new information in time and remove the old information which reduces the meaning of the information because of time lapse. Therefore, the model is closer to reality.展开更多
To predict the annual total yields of Chinese aquatic products in future five years ( 2011-2015) ,based on the theory and method of gray system,this paper firstly establishes a conventional GM ( 1,1) model and a gray ...To predict the annual total yields of Chinese aquatic products in future five years ( 2011-2015) ,based on the theory and method of gray system,this paper firstly establishes a conventional GM ( 1,1) model and a gray metabolic GM ( 1,1) model respectively to predict the annual total yields of Chinese aquatic products in 2006-2009 and compare the prediction accuracy between these two models. Then,it selects the model with higher accuracy to predict the annual total yields of Chinese aquatic products in future five years. The comparison indicates that gray metabolic GM ( 1,1) model has higher prediction accuracy and smaller error,thus it is more suitable for prediction of annual total yields of aquatic products. Therefore,it adopts the gray metabolic GM ( 1,1) model to predict annual total yields of Chinese aquatic products in 2011-2015. The prediction results of annual total yields are 55. 32,57. 46,59. 72,62. 02 and 64. 43 million tons respectively in future five years with annual average increase rate of about 3. 7% ,much higher than the objective of 2. 2% specified in the Twelfth Five-Year Plan of the National Fishery Development ( 2011 to 2015) . The results of this research show that the gray metabolic GM ( 1,1) model is suitable for prediction of yields of aquatic products and the total yields of Chinese aquatic products in 2011-2015 will totally be able to realize the objective of the Twelfth Five-Year Plan.展开更多
To create a new prediction model, the unbiased GM (1,1) model is optimized by the five-point slide method in this paper. Then, based on the occurrence areas of dce blast in Enshi District during 1995 -2004, the new ...To create a new prediction model, the unbiased GM (1,1) model is optimized by the five-point slide method in this paper. Then, based on the occurrence areas of dce blast in Enshi District during 1995 -2004, the new model and unbiased GM (1, 1 ) model are applied to predict the occurrence areas of rice blast during 2005 -2010. Predicting outcomes show that the prediction accuracy of five-point unbiased sliding optimized GM (1, 1 ) model is higher than the unbiased GM (1,1) model. Finally, combined with the prediction results, the author provides some suggestion for Enshi District in the prevention and control of rice blast in 2010.展开更多
Urban waste solids are now becoming one of the most crucial environmental problems. There are several different kinds of technologies normally used for waste solids disposal, among which landfill is more favorable in ...Urban waste solids are now becoming one of the most crucial environmental problems. There are several different kinds of technologies normally used for waste solids disposal, among which landfill is more favorable in China than others, especially for urban waste solids. Most of the design works up to now are based on a roughly estimation of the amount of urban waste solids without any theoretical support, which lead to a series problems. To meet the basic information requirements for the design work, the amount of the urban waste solids was predicted in this research by applying the gray theoretical model GM (1,1) through non linear differential equation simulation. The model parameters were estimated with the least square method (LSM) by running a certain MATALAB program, and the hypothesis test results show that the residual between the prediction value and the actual value approximately comply with the normal distribution N (0,0 21 2), and the probability of the residual within the range (-0 17, 0 19) is more than 95%, which indicate obviously that the model can be well used for the prediction of the amount of waste solids and those had been already testified by the latest two years data about the urban waste solids from Loudi City of China. With this model, the predicted amount of the waste solids produced in Loudi City in the next 30 years is 8049000 ton in total.展开更多
In grey system theory,the studies in the field of grey prediction model are focused on real number sequences,rather than grey number ones.Hereby,a prediction model based on interval grey number sequences is proposed.B...In grey system theory,the studies in the field of grey prediction model are focused on real number sequences,rather than grey number ones.Hereby,a prediction model based on interval grey number sequences is proposed.By mining the geometric features of interval grey number sequences on a two-dimensional surface,all the interval grey numbers are converted into real numbers by means of certain algorithm,and then the prediction model is established based on those real number sequences.The entire process avoids the algebraic operations of grey number,and the prediction problem of interval grey number is usefully solved.Ultimately,through an example's program simulation,the validity and practicability of this novel model are verified.展开更多
This paper expresses the efficient outputs of decisionmaking unit(DMU) as the sum of "average outputs" forecasted by a GM(1,N) model and "increased outputs" which reflect the difficulty to realize efficient ou...This paper expresses the efficient outputs of decisionmaking unit(DMU) as the sum of "average outputs" forecasted by a GM(1,N) model and "increased outputs" which reflect the difficulty to realize efficient outputs.The increased outputs are solved by linear programming using data envelopment analysis efficiency theories,wherein a new sample is introduced whose inputs are equal to the budget in the issue No.n + 1 and outputs are forecasted by the GM(1,N) model.The shortcoming in the existing methods that the forecasted efficient outputs may be less than the possible actual outputs according to developing trends of input-output rate in the periods of pre-n is overcome.The new prediction method provides decision-makers with more decisionmaking information,and the initial conditions are easy to be given.展开更多
The impulse waves induced by large-reservoir landslides can be characterized by a low Froude number.However,systematic research on predictive models specifically targeting the initial primary wave is lacking.Taking th...The impulse waves induced by large-reservoir landslides can be characterized by a low Froude number.However,systematic research on predictive models specifically targeting the initial primary wave is lacking.Taking the Shuipingzi 1#landslide that occurred in the Baihetan Reservoir area of the Jinsha River in China as an engineering example,this study established a large-scale physical model(with dimensions of 30 m×29 m×3.5 m at a scale of 1:150)and conducted scaled experiments on 3D landslide-induced impulse waves.During the process in which a sliding mass displaced and compressed a body of water to generate waves,the maximum initial wave amplitude was found to be positively correlated with the sliding velocity and the volume of the landslide.With the increase in the water depth,the wave amplitude initially increased and then decreased.The duration of pressure exertion by the sliding mass at its maximum velocity directly correlated with an elevated wave amplitude.Based on the theories of low-amplitude waves and energy conservation,while considering the energy conversion efficiency,a predictive model for the initial wave amplitude was derived.This model could fit and validate the functions of wavelength and wave velocity.The accuracy of the initial wave amplitude was verified using physical experiment data,with a prediction accuracy for the maximum initial wave amplitude reaching 90%.The conversion efficiency(η)directly determined the accuracy of the estimation formula.Under clear conditions for landslide-induced impulse wave generation,estimating the value ofηthrough analogy cases was feasible.This study has derived the landslide-induced impulse waves amplitude prediction formula from the standpoints of wave theory and energy conservation,with greater consideration given to the intrinsic characteristics in the formation process of landslide-induced impulse waves,thereby enhancing the applicability and extensibility of the formula.This can facilitate the development of empirical estimation methods for landslide-induced impulse waves toward universality.展开更多
The initial errors constitute one of the main limiting factors in the ability to predict the E1 Nino-Southem Oscillation (ENSO) in ocean-atmosphere coupled models. The conditional nonlinear optimal perturbation (C...The initial errors constitute one of the main limiting factors in the ability to predict the E1 Nino-Southem Oscillation (ENSO) in ocean-atmosphere coupled models. The conditional nonlinear optimal perturbation (CNOP) approach was em- ployed to study the largest initial error growth in the E1 Nino predictions of an intermediate coupled model (ICM). The optimal initial errors (as represented by CNOPs) in sea surface temperature anomalies (SSTAs) and sea level anomalies (SLAs) were obtained with seasonal variation. The CNOP-induced perturbations, which tend to evolve into the La Nifia mode, were found to have the same dynamics as ENSO itself. This indicates that, if CNOP-type errors are present in the initial conditions used to make a prediction of E1 Nino, the E1 Nino event tends to be under-predicted. In particular, compared with other seasonal CNOPs, the CNOPs in winter can induce the largest error growth, which gives rise to an ENSO amplitude that is hardly ever predicted accurately. Additionally, it was found that the CNOP-induced perturbations exhibit a strong spring predictability barrier (SPB) phenomenon for ENSO prediction. These results offer a way to enhance ICM prediction skill and, particularly, weaken the SPB phenomenon by filtering the CNOP-type errors in the initial state. The characteristic distributions of the CNOPs derived from the ICM also provide useful information for targeted observations through data assimilation. Given the fact that the derived CNOPs are season-dependent, it is suggested that seasonally varying targeted observations should be implemented to accurately predict ENSO events.展开更多
This research explores the potential for the evaluation and prediction of earth pressure balance shield performance based on a gray system model.The research focuses on a shield tunnel excavated for Metro Line 2 in Da...This research explores the potential for the evaluation and prediction of earth pressure balance shield performance based on a gray system model.The research focuses on a shield tunnel excavated for Metro Line 2 in Dalian,China.Due to the large error between the initial geological exploration data and real strata,the project construction is extremely difficult.In view of the current situation regarding the project,a quantitative method for evaluating the tunneling efficiency was proposed using cutterhead rotation(R),advance speed(S),total thrust(F)and torque(T).A total of 80 datasets with three input parameters and one output variable(F or T)were collected from this project,and a prediction framework based gray system model was established.Based on the prediction model,five prediction schemes were set up.Through error analysis,the optimal prediction scheme was obtained from the five schemes.The parametric investigation performed indicates that the relationships between F and the three input variables in the gray system model harmonize with the theoretical explanation.The case shows that the shield tunneling performance and efficiency are improved by the tunneling parameter prediction model based on the gray system model.展开更多
文摘The gray renewal GM (1,1) landslide prediction model was established by improving the gray model. Based on the established model, the author has made prediction of landslide deformation to the Xiangjiapo landslide and the Lianziya dangerous rock body. The results show that the gray renewal GM (1,1) model can supplement the new information in time and remove the old information which reduces the meaning of the information because of time lapse. Therefore, the model is closer to reality.
基金Supported by Special Project for Construction of Modern Agricultural Industrial Technology System(Grant No.:CARS-46-05)Scientific and Technological Project of Huazhong Agricultural University(Grant No.:52902-0900206038)National Natural Science Foundation of China(Grant No:31201719)
文摘To predict the annual total yields of Chinese aquatic products in future five years ( 2011-2015) ,based on the theory and method of gray system,this paper firstly establishes a conventional GM ( 1,1) model and a gray metabolic GM ( 1,1) model respectively to predict the annual total yields of Chinese aquatic products in 2006-2009 and compare the prediction accuracy between these two models. Then,it selects the model with higher accuracy to predict the annual total yields of Chinese aquatic products in future five years. The comparison indicates that gray metabolic GM ( 1,1) model has higher prediction accuracy and smaller error,thus it is more suitable for prediction of annual total yields of aquatic products. Therefore,it adopts the gray metabolic GM ( 1,1) model to predict annual total yields of Chinese aquatic products in 2011-2015. The prediction results of annual total yields are 55. 32,57. 46,59. 72,62. 02 and 64. 43 million tons respectively in future five years with annual average increase rate of about 3. 7% ,much higher than the objective of 2. 2% specified in the Twelfth Five-Year Plan of the National Fishery Development ( 2011 to 2015) . The results of this research show that the gray metabolic GM ( 1,1) model is suitable for prediction of yields of aquatic products and the total yields of Chinese aquatic products in 2011-2015 will totally be able to realize the objective of the Twelfth Five-Year Plan.
基金Supported by Science Research Project of Department of Education of Hubei Province (B20092901)~~
文摘To create a new prediction model, the unbiased GM (1,1) model is optimized by the five-point slide method in this paper. Then, based on the occurrence areas of dce blast in Enshi District during 1995 -2004, the new model and unbiased GM (1, 1 ) model are applied to predict the occurrence areas of rice blast during 2005 -2010. Predicting outcomes show that the prediction accuracy of five-point unbiased sliding optimized GM (1, 1 ) model is higher than the unbiased GM (1,1) model. Finally, combined with the prediction results, the author provides some suggestion for Enshi District in the prevention and control of rice blast in 2010.
文摘Urban waste solids are now becoming one of the most crucial environmental problems. There are several different kinds of technologies normally used for waste solids disposal, among which landfill is more favorable in China than others, especially for urban waste solids. Most of the design works up to now are based on a roughly estimation of the amount of urban waste solids without any theoretical support, which lead to a series problems. To meet the basic information requirements for the design work, the amount of the urban waste solids was predicted in this research by applying the gray theoretical model GM (1,1) through non linear differential equation simulation. The model parameters were estimated with the least square method (LSM) by running a certain MATALAB program, and the hypothesis test results show that the residual between the prediction value and the actual value approximately comply with the normal distribution N (0,0 21 2), and the probability of the residual within the range (-0 17, 0 19) is more than 95%, which indicate obviously that the model can be well used for the prediction of the amount of waste solids and those had been already testified by the latest two years data about the urban waste solids from Loudi City of China. With this model, the predicted amount of the waste solids produced in Loudi City in the next 30 years is 8049000 ton in total.
基金supported by the National Natural Science Foundation of China(7084001290924022)the Ph.D.Thesis Innovation and Excellent Foundation of Nanjing University of Aeronautics and Astronautics(2010)
文摘In grey system theory,the studies in the field of grey prediction model are focused on real number sequences,rather than grey number ones.Hereby,a prediction model based on interval grey number sequences is proposed.By mining the geometric features of interval grey number sequences on a two-dimensional surface,all the interval grey numbers are converted into real numbers by means of certain algorithm,and then the prediction model is established based on those real number sequences.The entire process avoids the algebraic operations of grey number,and the prediction problem of interval grey number is usefully solved.Ultimately,through an example's program simulation,the validity and practicability of this novel model are verified.
基金supported by the Research Start Funds for Introducing High-level Talents of North China University of Water Resources and Electric Power
文摘This paper expresses the efficient outputs of decisionmaking unit(DMU) as the sum of "average outputs" forecasted by a GM(1,N) model and "increased outputs" which reflect the difficulty to realize efficient outputs.The increased outputs are solved by linear programming using data envelopment analysis efficiency theories,wherein a new sample is introduced whose inputs are equal to the budget in the issue No.n + 1 and outputs are forecasted by the GM(1,N) model.The shortcoming in the existing methods that the forecasted efficient outputs may be less than the possible actual outputs according to developing trends of input-output rate in the periods of pre-n is overcome.The new prediction method provides decision-makers with more decisionmaking information,and the initial conditions are easy to be given.
基金The authors would like thank LI Renjiang and HU Bin from the China Three Gorges Corporation for providing many valuable suggestions for the establishment of the physical models.This work was supported by the National Natural Science Foundation of China(No.U23A2045)the China Three Gorges Corporation(YM(BHT)/(22)022)the Scientific Research Project of Chongqing Municipal Bureau of Planning and Natural Resources(Evaluation and Reinforcement Technology of Surge Disaster Caused by High and Steep Dangerous Rocks in Chongqing Reservoir Area of the Three Gorges Project,KJ-2023046).
文摘The impulse waves induced by large-reservoir landslides can be characterized by a low Froude number.However,systematic research on predictive models specifically targeting the initial primary wave is lacking.Taking the Shuipingzi 1#landslide that occurred in the Baihetan Reservoir area of the Jinsha River in China as an engineering example,this study established a large-scale physical model(with dimensions of 30 m×29 m×3.5 m at a scale of 1:150)and conducted scaled experiments on 3D landslide-induced impulse waves.During the process in which a sliding mass displaced and compressed a body of water to generate waves,the maximum initial wave amplitude was found to be positively correlated with the sliding velocity and the volume of the landslide.With the increase in the water depth,the wave amplitude initially increased and then decreased.The duration of pressure exertion by the sliding mass at its maximum velocity directly correlated with an elevated wave amplitude.Based on the theories of low-amplitude waves and energy conservation,while considering the energy conversion efficiency,a predictive model for the initial wave amplitude was derived.This model could fit and validate the functions of wavelength and wave velocity.The accuracy of the initial wave amplitude was verified using physical experiment data,with a prediction accuracy for the maximum initial wave amplitude reaching 90%.The conversion efficiency(η)directly determined the accuracy of the estimation formula.Under clear conditions for landslide-induced impulse wave generation,estimating the value ofηthrough analogy cases was feasible.This study has derived the landslide-induced impulse waves amplitude prediction formula from the standpoints of wave theory and energy conservation,with greater consideration given to the intrinsic characteristics in the formation process of landslide-induced impulse waves,thereby enhancing the applicability and extensibility of the formula.This can facilitate the development of empirical estimation methods for landslide-induced impulse waves toward universality.
基金supported by the National Natural Science Foundation of China (NFSC Grant Nos. 41690122, 41690120, 41490644, 41490640 and 41475101)+5 种基金the Ao Shan Talents Program supported by Qingdao National Laboratory for Marine Science and Technology (Grant No. 2015ASTP)a Chinese Academy of Sciences Strategic Priority Projectthe Western Pacific Ocean System (Grant Nos. XDA11010105, XDA11020306)the NSFC–Shandong Joint Fund for Marine Science Research Centers (Grant No. U1406401)the National Natural Science Foundation of China Innovative Group Grant (Grant No. 41421005)the Taishan Scholarship and Qingdao Innovative Program (Grant No. 2014GJJS0101)
文摘The initial errors constitute one of the main limiting factors in the ability to predict the E1 Nino-Southem Oscillation (ENSO) in ocean-atmosphere coupled models. The conditional nonlinear optimal perturbation (CNOP) approach was em- ployed to study the largest initial error growth in the E1 Nino predictions of an intermediate coupled model (ICM). The optimal initial errors (as represented by CNOPs) in sea surface temperature anomalies (SSTAs) and sea level anomalies (SLAs) were obtained with seasonal variation. The CNOP-induced perturbations, which tend to evolve into the La Nifia mode, were found to have the same dynamics as ENSO itself. This indicates that, if CNOP-type errors are present in the initial conditions used to make a prediction of E1 Nino, the E1 Nino event tends to be under-predicted. In particular, compared with other seasonal CNOPs, the CNOPs in winter can induce the largest error growth, which gives rise to an ENSO amplitude that is hardly ever predicted accurately. Additionally, it was found that the CNOP-induced perturbations exhibit a strong spring predictability barrier (SPB) phenomenon for ENSO prediction. These results offer a way to enhance ICM prediction skill and, particularly, weaken the SPB phenomenon by filtering the CNOP-type errors in the initial state. The characteristic distributions of the CNOPs derived from the ICM also provide useful information for targeted observations through data assimilation. Given the fact that the derived CNOPs are season-dependent, it is suggested that seasonally varying targeted observations should be implemented to accurately predict ENSO events.
基金support by the National Natural Science Foundation of China(Grant Nos.52108377,52090084,and 51938008).
文摘This research explores the potential for the evaluation and prediction of earth pressure balance shield performance based on a gray system model.The research focuses on a shield tunnel excavated for Metro Line 2 in Dalian,China.Due to the large error between the initial geological exploration data and real strata,the project construction is extremely difficult.In view of the current situation regarding the project,a quantitative method for evaluating the tunneling efficiency was proposed using cutterhead rotation(R),advance speed(S),total thrust(F)and torque(T).A total of 80 datasets with three input parameters and one output variable(F or T)were collected from this project,and a prediction framework based gray system model was established.Based on the prediction model,five prediction schemes were set up.Through error analysis,the optimal prediction scheme was obtained from the five schemes.The parametric investigation performed indicates that the relationships between F and the three input variables in the gray system model harmonize with the theoretical explanation.The case shows that the shield tunneling performance and efficiency are improved by the tunneling parameter prediction model based on the gray system model.