The geologic conditions of superimposed basins in China are very complicated. This is mainly shown by multi-phase structural evolution, multiple sets of source-reservoir-cap rock combinations, multiple stages of hydro...The geologic conditions of superimposed basins in China are very complicated. This is mainly shown by multi-phase structural evolution, multiple sets of source-reservoir-cap rock combinations, multiple stages of hydrocarbon generation and expulsion from source rocks, multi-cycle hydrocarbon enrichment and accumulation, and multi-phase reservoir adjustment and reconstruction. The enrichment, accumulation and distribution of hydrocarbon is mainly controlled by the source rock kitchen, paleo- anticline, regional cap rock and intensity of tectonic movement. In this paper, the T-BCMS model has been developed to predict favorable areas of hydrocarbon accumulation in complicated superimposed basins according to time and spatial relationships among five key factors. The five factors include unconformity surface representing tectonic balancing （B）, regional cap rock representing hydrocarbon protection （C）, paleo-anticline representing hydrocarbon migration and accumulation （M）, source rock kitchen representing hydrocarbon generation and expulsion （S） and geological time （T）. There are three necessary conditions to form favorable areas of hydrocarbon accumulation. First, four key factors BCMS should be strictly in the order of BCMS from top to bottom. Second, superimposition of four key factors BCMS in the same area is the most favorable for hydrocarbon accumulation. Third, vertically ordered combination and superimposition in the same area of BCMS should occur at the same geological time. The model has been used to predict the most favorable exploration areas in Ordovician in the Tarim Basin in the main hydrocarbon accumulation periods. The result shows that 95% of the discovered Ordovician hydrocarbon reservoirs are located in the predicted areas, which indicates the feasibility and reliability of the key factor matching T-BCMS model for hydrocarbon accumulation and enrichment.展开更多
This study firstly improved the Generalized Autoregressive Conditional Heteroskedast model for the issue that financial product sales data have singular information when applying this model, and the improved outlier d...This study firstly improved the Generalized Autoregressive Conditional Heteroskedast model for the issue that financial product sales data have singular information when applying this model, and the improved outlier detection method was used to detect the location of outliers, which were processed by the iterative method. Secondly, in order to describe the peak and fat tail of the financial time series, as well as the leverage effect, this work used the skewed-t Asymmetric Power Autoregressive Conditional Heteroskedasticity model based on the Autoregressive Integrated Moving Average Model to analyze the sales data. Empirical analysis showed that the model considering the skewed distribution is effective.展开更多
Generalized linear mixed models (GLMMs) are typically constructed by incorporating random effects into the linear predictor. The random effects are usually assumed to be normally distributed with mean zero and varianc...Generalized linear mixed models (GLMMs) are typically constructed by incorporating random effects into the linear predictor. The random effects are usually assumed to be normally distributed with mean zero and variance-covariance identity matrix. In this paper, we propose to release random effects to non-normal distributions and discuss how to model the mean and covariance structures in GLMMs simultaneously. Parameter estimation is solved by using Quasi-Monte Carlo (QMC) method through iterative Newton-Raphson (NR) algorithm very well in terms of accuracy and stabilization, which is demonstrated by real binary salamander mating data analysis and simulation studies.展开更多
A new modeling approach for nonlinear systems with rate-dependent hysteresis is proposed. The approach is used for the modeling of the giant magnetostrictive actuator, which has the rate-dependent nonlinear property. ...A new modeling approach for nonlinear systems with rate-dependent hysteresis is proposed. The approach is used for the modeling of the giant magnetostrictive actuator, which has the rate-dependent nonlinear property. The models built are simpler than the existed approaches. Compared with the experiment result, the model built can well describe the hysteresis nonlinear of the actuator for input signals with complex frequency. An adaptive direct inverse control approach is proposed based on the fuzzy tree model and inverse learning and special learning that are used in neural network broadly. In this approach, the inverse model of the plant is identified to be the initial controller firstly. Then, the inverse model is connected with the plant in series and the linear parameters of the controller are adjusted using the least mean square algorithm by on-line manner. The direct inverse control approach based on the fuzzy tree model is applied on the tracing control of the actuator by simulation. The simulation results show the correctness of the approach.展开更多
The local influence analysis is an important problem in statistical inference and some models have been discussed in many literatures This paper deals with the problem of assessing local influences in a multivariate t...The local influence analysis is an important problem in statistical inference and some models have been discussed in many literatures This paper deals with the problem of assessing local influences in a multivariate t-model with Rao's simple struc-ture(RSS). Based on Cook's likelihood displacement, the effects of some minor perturbation on the statistical inference is assessed. As an application, a common covariance-weighted perturbation is thoroughly discussed.展开更多
In this paper, a Takagi Sugeno （T-S） fuzzy model-based method is proposed to deal with the problem of synchronization of two identical or different hyperchaotic systems. The T S fuzzy models with a small number of f...In this paper, a Takagi Sugeno （T-S） fuzzy model-based method is proposed to deal with the problem of synchronization of two identical or different hyperchaotic systems. The T S fuzzy models with a small number of fuzzy IF-THEN rules are employed to represent many typical hyperchaotic systems exactly. The benefit of employing the T-S fuzzy models lies in mathematical simplicity of analysis. Based on the T-S fuzzy hyperchaotic models, two fuzzy controllers arc designed via parallel distributed compensation （PDC） and exact linearization （EL） techniques to synchronize two identical hyperchaotic systems with uncertain parameters and two different hyperchaotic systems, respectively. The sufficient conditions for the robust synchronization of two identical hyperchaotic systems with uncertain parameters and the asymptotic synchronization of two different hyperchaotic systems are derived by applying the Lyapunov stability theory. This method is a universal one of synchronizing two identical or different hyperchaotic systems. Numerical examples are given to demonstrate the validity of the proposed fuzzy model and hyperchaotic synchronization scheme.展开更多
The study of plant species abundance distribution(SAD)in natural communities is of considerable importance to understand the processes and ecological rules of community assembly.With the distribution of tree,shrub and...The study of plant species abundance distribution(SAD)in natural communities is of considerable importance to understand the processes and ecological rules of community assembly.With the distribution of tree,shrub and herb layers of eight natural communities of Toona ciliata as research targets,three diff erent ecological niche models were used:broken stick model,overlapping niche model and niche preemption model,as well as three statistical models:log-series distribution model,log-normal distribution model and Weibull distribution model,to fi t SAD of the diff erent vegetation layers based on data collected.Goodness-of-fi t was compared with Chi square test,Kolmogorov–Smirnov(K–S)test and Akaike Information Criterion(AIC).The results show:(1)based on the criteria of the lowest AIC value,Chi square value and K–S value with no signifi cant diff erence(p>0.05)between theoretic and observed SADs.The suitability and goodness-of-fi t of the broken stick model was the best of three ecological niche models.The log-series distribution model did not accept the fi tted results of most vegetation layers and had the lowest goodness-of-fi t.The Weibull distribution model had the best goodness-of-fi t for SADs.Overall,the statistical SADs performed better than the ecological ones.(2)T.ciliata was the dominant species in all the communities;species richness and diversity of herbs were the highest of the vegetation layers,while the diversities of the tree layers were slightly higher than the shrub layers;there were fewer common species and more rare species in the eight communities.The herb layers had the highest community evenness,followed by the shrub and the tree layers.Due to the complexity and habitat diversity of the diff erent T.ciliata communities,comprehensive analyses of a variety of SADs and tests for optimal models together with management,are practical steps to enhance understanding of ecological processes and mechanisms of T.ciliata communities,to detect disturbances,and to facilitate biodiversity and species conservation.展开更多
The study of flow diversions in open channels plays an important practical role in the design and management of open-channel networks for irrigation or drainage. To accurately predict the mean flow and turbulence char...The study of flow diversions in open channels plays an important practical role in the design and management of open-channel networks for irrigation or drainage. To accurately predict the mean flow and turbulence characteristics of open-channel dividing flows, a hybrid LES-RANS model, which combines the large eddy simulation （LES） model with the Reynolds-averaged Navier-Stokes （RANS） model, is proposed in the present study. The unsteady RANS model was used to simulate the upstream and downstream regions of a main channel, as well as the downstream region of a branch channel. The LES model was used to simulate the channel diversion region, where turbulent flow characteristics are complicated. Isotropic velocity fluctuations were added at the inflow interface of the LES region to trigger the generation of resolved turbulence. A method based on the virtual body force is proposed to impose Reynolds-averaged velocity fields near the outlet of the LES region in order to take downstream flow effects computed by the RANS model into account and dissipate the excessive turbulent fluctuations. This hybrid approach saves computational effort and makes it easier to properly specify inlet and outlet boundary conditions. Comparison between computational results and experimental data indicates that this relatively new modeling approach can accurately predict open-channel T-diversion flows.展开更多
基金supported by the National Basic Research Program (2006CB202308)
文摘The geologic conditions of superimposed basins in China are very complicated. This is mainly shown by multi-phase structural evolution, multiple sets of source-reservoir-cap rock combinations, multiple stages of hydrocarbon generation and expulsion from source rocks, multi-cycle hydrocarbon enrichment and accumulation, and multi-phase reservoir adjustment and reconstruction. The enrichment, accumulation and distribution of hydrocarbon is mainly controlled by the source rock kitchen, paleo- anticline, regional cap rock and intensity of tectonic movement. In this paper, the T-BCMS model has been developed to predict favorable areas of hydrocarbon accumulation in complicated superimposed basins according to time and spatial relationships among five key factors. The five factors include unconformity surface representing tectonic balancing （B）, regional cap rock representing hydrocarbon protection （C）, paleo-anticline representing hydrocarbon migration and accumulation （M）, source rock kitchen representing hydrocarbon generation and expulsion （S） and geological time （T）. There are three necessary conditions to form favorable areas of hydrocarbon accumulation. First, four key factors BCMS should be strictly in the order of BCMS from top to bottom. Second, superimposition of four key factors BCMS in the same area is the most favorable for hydrocarbon accumulation. Third, vertically ordered combination and superimposition in the same area of BCMS should occur at the same geological time. The model has been used to predict the most favorable exploration areas in Ordovician in the Tarim Basin in the main hydrocarbon accumulation periods. The result shows that 95% of the discovered Ordovician hydrocarbon reservoirs are located in the predicted areas, which indicates the feasibility and reliability of the key factor matching T-BCMS model for hydrocarbon accumulation and enrichment.
文摘This study firstly improved the Generalized Autoregressive Conditional Heteroskedast model for the issue that financial product sales data have singular information when applying this model, and the improved outlier detection method was used to detect the location of outliers, which were processed by the iterative method. Secondly, in order to describe the peak and fat tail of the financial time series, as well as the leverage effect, this work used the skewed-t Asymmetric Power Autoregressive Conditional Heteroskedasticity model based on the Autoregressive Integrated Moving Average Model to analyze the sales data. Empirical analysis showed that the model considering the skewed distribution is effective.
文摘Generalized linear mixed models (GLMMs) are typically constructed by incorporating random effects into the linear predictor. The random effects are usually assumed to be normally distributed with mean zero and variance-covariance identity matrix. In this paper, we propose to release random effects to non-normal distributions and discuss how to model the mean and covariance structures in GLMMs simultaneously. Parameter estimation is solved by using Quasi-Monte Carlo (QMC) method through iterative Newton-Raphson (NR) algorithm very well in terms of accuracy and stabilization, which is demonstrated by real binary salamander mating data analysis and simulation studies.
基金Supported by the National Natural Science Foundation of China (Grant No. 60534020)the National Basic Research Program of China (GrantNo. G2002cb312205-04)+1 种基金the Research Fund for the Doctoral Program of Higher Education (Grant No. 20070006060)the Key Subject Foundation of Beijing (Grant Nos. XK100060526, XK100060422)
文摘A new modeling approach for nonlinear systems with rate-dependent hysteresis is proposed. The approach is used for the modeling of the giant magnetostrictive actuator, which has the rate-dependent nonlinear property. The models built are simpler than the existed approaches. Compared with the experiment result, the model built can well describe the hysteresis nonlinear of the actuator for input signals with complex frequency. An adaptive direct inverse control approach is proposed based on the fuzzy tree model and inverse learning and special learning that are used in neural network broadly. In this approach, the inverse model of the plant is identified to be the initial controller firstly. Then, the inverse model is connected with the plant in series and the linear parameters of the controller are adjusted using the least mean square algorithm by on-line manner. The direct inverse control approach based on the fuzzy tree model is applied on the tracing control of the actuator by simulation. The simulation results show the correctness of the approach.
文摘The local influence analysis is an important problem in statistical inference and some models have been discussed in many literatures This paper deals with the problem of assessing local influences in a multivariate t-model with Rao's simple struc-ture(RSS). Based on Cook's likelihood displacement, the effects of some minor perturbation on the statistical inference is assessed. As an application, a common covariance-weighted perturbation is thoroughly discussed.
基金Project supported by the National Natural Science Foundation of China (Grant Nos 60534010, 60572070, 60774048 and 60728307)the Program for Changjiang Scholars and Innovative Research Groups of China (Grant No 60521003)+1 种基金the Specialized Research Fund for the Doctoral Program of Higher Education of China (Grant No 20070145015)the National High Technology Research and Development Program of China (Grant No 2006AA04Z183)
文摘In this paper, a Takagi Sugeno （T-S） fuzzy model-based method is proposed to deal with the problem of synchronization of two identical or different hyperchaotic systems. The T S fuzzy models with a small number of fuzzy IF-THEN rules are employed to represent many typical hyperchaotic systems exactly. The benefit of employing the T-S fuzzy models lies in mathematical simplicity of analysis. Based on the T-S fuzzy hyperchaotic models, two fuzzy controllers arc designed via parallel distributed compensation （PDC） and exact linearization （EL） techniques to synchronize two identical hyperchaotic systems with uncertain parameters and two different hyperchaotic systems, respectively. The sufficient conditions for the robust synchronization of two identical hyperchaotic systems with uncertain parameters and the asymptotic synchronization of two different hyperchaotic systems are derived by applying the Lyapunov stability theory. This method is a universal one of synchronizing two identical or different hyperchaotic systems. Numerical examples are given to demonstrate the validity of the proposed fuzzy model and hyperchaotic synchronization scheme.
基金Hubei Provincial Department of Science and Technology,under the public welfare research project[No.402012DBA40001]Hubei Provincial Department of Education,under the scientifi c research project[No.B20160555].
文摘The study of plant species abundance distribution(SAD)in natural communities is of considerable importance to understand the processes and ecological rules of community assembly.With the distribution of tree,shrub and herb layers of eight natural communities of Toona ciliata as research targets,three diff erent ecological niche models were used:broken stick model,overlapping niche model and niche preemption model,as well as three statistical models:log-series distribution model,log-normal distribution model and Weibull distribution model,to fi t SAD of the diff erent vegetation layers based on data collected.Goodness-of-fi t was compared with Chi square test,Kolmogorov–Smirnov(K–S)test and Akaike Information Criterion(AIC).The results show:(1)based on the criteria of the lowest AIC value,Chi square value and K–S value with no signifi cant diff erence(p>0.05)between theoretic and observed SADs.The suitability and goodness-of-fi t of the broken stick model was the best of three ecological niche models.The log-series distribution model did not accept the fi tted results of most vegetation layers and had the lowest goodness-of-fi t.The Weibull distribution model had the best goodness-of-fi t for SADs.Overall,the statistical SADs performed better than the ecological ones.(2)T.ciliata was the dominant species in all the communities;species richness and diversity of herbs were the highest of the vegetation layers,while the diversities of the tree layers were slightly higher than the shrub layers;there were fewer common species and more rare species in the eight communities.The herb layers had the highest community evenness,followed by the shrub and the tree layers.Due to the complexity and habitat diversity of the diff erent T.ciliata communities,comprehensive analyses of a variety of SADs and tests for optimal models together with management,are practical steps to enhance understanding of ecological processes and mechanisms of T.ciliata communities,to detect disturbances,and to facilitate biodiversity and species conservation.
文摘The study of flow diversions in open channels plays an important practical role in the design and management of open-channel networks for irrigation or drainage. To accurately predict the mean flow and turbulence characteristics of open-channel dividing flows, a hybrid LES-RANS model, which combines the large eddy simulation （LES） model with the Reynolds-averaged Navier-Stokes （RANS） model, is proposed in the present study. The unsteady RANS model was used to simulate the upstream and downstream regions of a main channel, as well as the downstream region of a branch channel. The LES model was used to simulate the channel diversion region, where turbulent flow characteristics are complicated. Isotropic velocity fluctuations were added at the inflow interface of the LES region to trigger the generation of resolved turbulence. A method based on the virtual body force is proposed to impose Reynolds-averaged velocity fields near the outlet of the LES region in order to take downstream flow effects computed by the RANS model into account and dissipate the excessive turbulent fluctuations. This hybrid approach saves computational effort and makes it easier to properly specify inlet and outlet boundary conditions. Comparison between computational results and experimental data indicates that this relatively new modeling approach can accurately predict open-channel T-diversion flows.
