Variable Rate Technology （VRT） takes within-field variability into consideration and aims to match resource application to crop requirement. Even though Texas is the most important cotton producing state in the US, ...Variable Rate Technology （VRT） takes within-field variability into consideration and aims to match resource application to crop requirement. Even though Texas is the most important cotton producing state in the US, the rate of VRT adoption is very low here. Hence, analyzing the factors influencing the adoption and providing a regional estimate of the impact of VRT adoption on cotton yield is very important. This study used the 2009 Southern Cotton Precision Farming Survey to analyze the farm and farmer characteristics affecting the adoption of VRT among Texas cotton farmers and to empirically estimate the impact of adoption of VRT on cotton yield in Texas. A two-stage least square procedure with a logistic regression model in the first stage and a multiple linear regression model in the second stage was used to analyze the data. The study revealed that there are significant regional differences in adoption pattern within the state of Texas; and the farmers from the coastal region, where there is higher within-field variability, were more likely to adopt VRT compared to other regions. Younger farmers, farmers managing larger farms, and farmers who use computers for farming operations were more likely to adopt VRT. The results also showed that, on an average, the adoption of VRT does not lead to significant yield improvements for cotton in Texas. Since the impact of VRT adoption on yield is not significant, the source of economic advantage of VRT adoption in Texas may be the reduction of input cost.展开更多
An integrated nonlinear planning(NLP) model is built for space station long-duration orbital missions considering both the vehicle visiting schedules and the interaction effects between target phasing,vehicle return a...An integrated nonlinear planning(NLP) model is built for space station long-duration orbital missions considering both the vehicle visiting schedules and the interaction effects between target phasing,vehicle return adjusting and Earth observation aiming.A two-level optimization approach is proposed to solve this complicated problem.The up-level problem employs the launch times of visiting vehicles as design variables,considers the constraints of crew rotations,resource resupplies and rendezvous launch windows,and is solved by a genetic algorithm.The low-level problems employ the maneuver impulses and burn times within each orbital mission as design variables,and a high-efficient shooting iteration method is proposed based on an analytical equation for the phase angle correction considering the J 2 perturbation.The results indicate that the integrated NLP model for space station long-duration orbital missions is effective,and the proposed optimization approach can obtain the optimal solutions that satisfy the multiple constraints and reduce the total propellant consumption.展开更多
This paper studies the parameter estimation of multiple dimensional linear errors-in-variables (EV) models in the case where replicated observations are available in some experimental points. Asymptotic normality is e...This paper studies the parameter estimation of multiple dimensional linear errors-in-variables (EV) models in the case where replicated observations are available in some experimental points. Asymptotic normality is established under mild conditions, and the parameters entering the asymptotic variance are consistently estimated to render the result useable in the construction of large-sample confidence regions.展开更多
This paper analyzes the dynamics of nonlinear multivariate time series models that is represented by generalized impulse response functions and asymmetric functions. We illustrate the measures of shock persistences an...This paper analyzes the dynamics of nonlinear multivariate time series models that is represented by generalized impulse response functions and asymmetric functions. We illustrate the measures of shock persistences and asymmetric effects of shocks derived from the generalized impulse response functions and asymmetric function in bivariate smooth transition regression models. The empirical work investigates a bivariate smooth transition model of US GDP and the unemployment rate.展开更多
文摘Variable Rate Technology （VRT） takes within-field variability into consideration and aims to match resource application to crop requirement. Even though Texas is the most important cotton producing state in the US, the rate of VRT adoption is very low here. Hence, analyzing the factors influencing the adoption and providing a regional estimate of the impact of VRT adoption on cotton yield is very important. This study used the 2009 Southern Cotton Precision Farming Survey to analyze the farm and farmer characteristics affecting the adoption of VRT among Texas cotton farmers and to empirically estimate the impact of adoption of VRT on cotton yield in Texas. A two-stage least square procedure with a logistic regression model in the first stage and a multiple linear regression model in the second stage was used to analyze the data. The study revealed that there are significant regional differences in adoption pattern within the state of Texas; and the farmers from the coastal region, where there is higher within-field variability, were more likely to adopt VRT compared to other regions. Younger farmers, farmers managing larger farms, and farmers who use computers for farming operations were more likely to adopt VRT. The results also showed that, on an average, the adoption of VRT does not lead to significant yield improvements for cotton in Texas. Since the impact of VRT adoption on yield is not significant, the source of economic advantage of VRT adoption in Texas may be the reduction of input cost.
基金supported by the National Natural Science Foundation of China(Grant No.11222215)the Foundation for the Author of National Excellent Doctoral Dissertation of China(Grant No.201171)
文摘An integrated nonlinear planning(NLP) model is built for space station long-duration orbital missions considering both the vehicle visiting schedules and the interaction effects between target phasing,vehicle return adjusting and Earth observation aiming.A two-level optimization approach is proposed to solve this complicated problem.The up-level problem employs the launch times of visiting vehicles as design variables,considers the constraints of crew rotations,resource resupplies and rendezvous launch windows,and is solved by a genetic algorithm.The low-level problems employ the maneuver impulses and burn times within each orbital mission as design variables,and a high-efficient shooting iteration method is proposed based on an analytical equation for the phase angle correction considering the J 2 perturbation.The results indicate that the integrated NLP model for space station long-duration orbital missions is effective,and the proposed optimization approach can obtain the optimal solutions that satisfy the multiple constraints and reduce the total propellant consumption.
基金This project is supported by the National Natural Science Foundation of China (No.19631040)
文摘This paper studies the parameter estimation of multiple dimensional linear errors-in-variables (EV) models in the case where replicated observations are available in some experimental points. Asymptotic normality is established under mild conditions, and the parameters entering the asymptotic variance are consistently estimated to render the result useable in the construction of large-sample confidence regions.
文摘This paper analyzes the dynamics of nonlinear multivariate time series models that is represented by generalized impulse response functions and asymmetric functions. We illustrate the measures of shock persistences and asymmetric effects of shocks derived from the generalized impulse response functions and asymmetric function in bivariate smooth transition regression models. The empirical work investigates a bivariate smooth transition model of US GDP and the unemployment rate.
