An SIS epidemic model with a simple vaccination is investigated in this article, The efficiency of vaccine, the disease-related death rate and population dynamics are also considered in this model. The authors find tw...An SIS epidemic model with a simple vaccination is investigated in this article, The efficiency of vaccine, the disease-related death rate and population dynamics are also considered in this model. The authors find two threshold R0 and Rc （Rc may not exist）. There is a unique endemic equilibrium for R0 〉 1 or Rc = R0; there are two endemic equilibria for Rc 〈 R0 〈 1; and there is no endemic equilibrium for Rn 〈 Rc 〈 1. When Rc exists, there is a backward bifurcation from the disease-free equilibrium for R0 = 1. They analyze the stability of equilibria and obtain the globally dynamic behaviors of the model. The results acquired in this article show that an accurate estimation of the efficiency of vaccine is necessary to prevent and controll the spread of disease.展开更多
A new variable time step method,which is called the backwards calculating time step method,is presented in this paper.It allows numerical simulation of soil freezing and thawing while avoiding "phase change missi...A new variable time step method,which is called the backwards calculating time step method,is presented in this paper.It allows numerical simulation of soil freezing and thawing while avoiding "phase change missing and overflowing".A sensitive heat capacity model is introduced through which the calculation errors are analyzed.Then the equation using the self-adjusted time step is presented and solved using finite differences.Through this equation,the time needed for a space cell to reach the phase change point temperature is calculated.Using this time allows the time step to be adjusted so that errors caused by "phase change missing and overflowing" are successfully eliminated.Above all,the obvious features of this method are an accelerated rate for adjusting the time step and simplifing the computations.An actual example proves that this method can accurately calculate the temperature fields during soil freezing and thawing.It is an improvement over traditional methods and can be widely used on complicated multi-dimensional phase change problems.展开更多
The goal of this work is to develop a hybrid electric vehicle model that is suitable for use in a dynamic programming algorithm that provides the benchmark for optimal control of the hybrid powertrain. The benchmark a...The goal of this work is to develop a hybrid electric vehicle model that is suitable for use in a dynamic programming algorithm that provides the benchmark for optimal control of the hybrid powertrain. The benchmark analysis employs dynamic programming by backward induction to determine the globally optimal solution by solving the energy management problem starting at the final timestep and proceeding backwards in time. This method requires the development of a backwards facing model that propagates the wheel speed of the vehicle for the given drive cycle through the driveline components to determine the operating points of the powertrain. Although dynamic programming only searches the solution space within the feasible regions of operation, the benchmarking model must be solved for every admissible state at every timestep leading to strict requirements for runtime and memory. The backward facing model employs the quasi-static assumption of powertrain operation to reduce the fidelity of the model to accommodate these requirements. Verification and validation testing of the dynamic programming algorithm is conducted to ensure successful operation of the algorithm and to assess the validity of the determined control policy against a high-fidelity forward-facing vehicle model with a percent difference of fuel consumption of 1.2%. The benchmark analysis is conducted over multiple drive cycles to determine the optimal control policy that provides a benchmark for real-time algorithm development and determines control trends that can be used to improve existing algorithms. The optimal combined charge sustaining fuel economy of the vehicle is determined by the dynamic programming algorithm to be 32.99 MPG, a 52.6% increase over the stock 3.6 L 2019 Chevrolet Blazer.展开更多
Aiming at the problem that the vehicles always turn left in advance which causes heavy conflicts in the intersection and effected traffic efficiency,the solution of the left-turn lane’s stop line backwards setting wa...Aiming at the problem that the vehicles always turn left in advance which causes heavy conflicts in the intersection and effected traffic efficiency,the solution of the left-turn lane’s stop line backwards setting was proposed,and the critical conditions on the stop line’s setting were studied.Firstly,we studied the characteristics of trajectories distribution in the release process of turning left in advance vehicles.Based on that,we proposed to move the stop line backwards to solve the problem of turning left in advance.Considering the intersection’s geometric features and the vehicle operation features,the geometric critical condition was given for setting the position of left-turn lane’s stop line.And then the model of left-turn vehicles’queuing length was established based on queuing theory and traffic wave theory.By using queuing length model,the flow restrictions of stop line backwards could be found.Assuming left-turn vehicles’arrival rate is stable in a certain period of time,the minimum green time and the maximum red time of left-turn phase were given after the stop line was set up.According to the changes of the vehicles’turning paths,the shortest yellow setting recommendation was given.Finally,the application of the critical limits used in stop line backwards setting was demonstrated.The research result could provide a theoretical basis for traffic signs and markings’setting and perfect the relevant laws and regulations.展开更多
In order to enhance the accuracy and reliability of wireless location under non-line-of-sight （NLOS） environments,a novel neural network （NN） location approach using the digital broadcasting signals is presented. ...In order to enhance the accuracy and reliability of wireless location under non-line-of-sight （NLOS） environments,a novel neural network （NN） location approach using the digital broadcasting signals is presented. By the learning ability of the NN and the closely approximate unknown function to any degree of desired accuracy,the input-output mapping relationship between coordinates and the measurement data of time of arrival （TOA） and time difference of arrival （TDOA） is established. A real-time learning algorithm based on the extended Kalman filter （EKF） is used to train the multilayer perceptron （MLP） network by treating the linkweights of a network as the states of the nonlinear dynamic system. Since the EKF-based learning algorithm approximately gives the minimum variance estimate of the linkweights,the convergence is improved in comparison with the backwards error propagation （BP） algorithm. Numerical results illustrate thatthe proposedalgorithmcanachieve enhanced accuracy,and the performance ofthe algorithmis betterthanthat of the BP-based NN algorithm and the least squares （LS） algorithm in the NLOS environments. Moreover,this location method does not depend on a particular distribution of the NLOS error and does not need line-of-sight （ LOS ） or NLOS identification.展开更多
The infinite-horizon linear quadratic regulation （LQR） problem is settled for discretetime systems with input delay. With the help of an autoregressive moving average （ARMA） innovation model, solutions to the unde...The infinite-horizon linear quadratic regulation （LQR） problem is settled for discretetime systems with input delay. With the help of an autoregressive moving average （ARMA） innovation model, solutions to the underlying problem are obtained. The design of the optimal control law involves in resolving one polynomial equation and one spectral factorization. The latter is the major obstacle of the present problem, and the reorganized innovation approach is used to clear it up. The calculation of spectral factorization finally comes down to solving two Riccati equations with the same dimension as the original systems.展开更多
基金Supported by the Nature Science Foundation of China(19971066)Postdoctoral Foundation of China(2005037785)
文摘An SIS epidemic model with a simple vaccination is investigated in this article, The efficiency of vaccine, the disease-related death rate and population dynamics are also considered in this model. The authors find two threshold R0 and Rc （Rc may not exist）. There is a unique endemic equilibrium for R0 〉 1 or Rc = R0; there are two endemic equilibria for Rc 〈 R0 〈 1; and there is no endemic equilibrium for Rn 〈 Rc 〈 1. When Rc exists, there is a backward bifurcation from the disease-free equilibrium for R0 = 1. They analyze the stability of equilibria and obtain the globally dynamic behaviors of the model. The results acquired in this article show that an accurate estimation of the efficiency of vaccine is necessary to prevent and controll the spread of disease.
基金Project 2006G1662-00 supported by the Key Science and Technology Project of Heilongjiang Province
文摘A new variable time step method,which is called the backwards calculating time step method,is presented in this paper.It allows numerical simulation of soil freezing and thawing while avoiding "phase change missing and overflowing".A sensitive heat capacity model is introduced through which the calculation errors are analyzed.Then the equation using the self-adjusted time step is presented and solved using finite differences.Through this equation,the time needed for a space cell to reach the phase change point temperature is calculated.Using this time allows the time step to be adjusted so that errors caused by "phase change missing and overflowing" are successfully eliminated.Above all,the obvious features of this method are an accelerated rate for adjusting the time step and simplifing the computations.An actual example proves that this method can accurately calculate the temperature fields during soil freezing and thawing.It is an improvement over traditional methods and can be widely used on complicated multi-dimensional phase change problems.
文摘The goal of this work is to develop a hybrid electric vehicle model that is suitable for use in a dynamic programming algorithm that provides the benchmark for optimal control of the hybrid powertrain. The benchmark analysis employs dynamic programming by backward induction to determine the globally optimal solution by solving the energy management problem starting at the final timestep and proceeding backwards in time. This method requires the development of a backwards facing model that propagates the wheel speed of the vehicle for the given drive cycle through the driveline components to determine the operating points of the powertrain. Although dynamic programming only searches the solution space within the feasible regions of operation, the benchmarking model must be solved for every admissible state at every timestep leading to strict requirements for runtime and memory. The backward facing model employs the quasi-static assumption of powertrain operation to reduce the fidelity of the model to accommodate these requirements. Verification and validation testing of the dynamic programming algorithm is conducted to ensure successful operation of the algorithm and to assess the validity of the determined control policy against a high-fidelity forward-facing vehicle model with a percent difference of fuel consumption of 1.2%. The benchmark analysis is conducted over multiple drive cycles to determine the optimal control policy that provides a benchmark for real-time algorithm development and determines control trends that can be used to improve existing algorithms. The optimal combined charge sustaining fuel economy of the vehicle is determined by the dynamic programming algorithm to be 32.99 MPG, a 52.6% increase over the stock 3.6 L 2019 Chevrolet Blazer.
基金the National Natural Science Foundation of China(Nos.51108208,512782520 and 51278220)
文摘Aiming at the problem that the vehicles always turn left in advance which causes heavy conflicts in the intersection and effected traffic efficiency,the solution of the left-turn lane’s stop line backwards setting was proposed,and the critical conditions on the stop line’s setting were studied.Firstly,we studied the characteristics of trajectories distribution in the release process of turning left in advance vehicles.Based on that,we proposed to move the stop line backwards to solve the problem of turning left in advance.Considering the intersection’s geometric features and the vehicle operation features,the geometric critical condition was given for setting the position of left-turn lane’s stop line.And then the model of left-turn vehicles’queuing length was established based on queuing theory and traffic wave theory.By using queuing length model,the flow restrictions of stop line backwards could be found.Assuming left-turn vehicles’arrival rate is stable in a certain period of time,the minimum green time and the maximum red time of left-turn phase were given after the stop line was set up.According to the changes of the vehicles’turning paths,the shortest yellow setting recommendation was given.Finally,the application of the critical limits used in stop line backwards setting was demonstrated.The research result could provide a theoretical basis for traffic signs and markings’setting and perfect the relevant laws and regulations.
基金supported by National Natural Science Foundation of China(Grant No.11301191)supported by Science and Technology Development Fund(Macao S.A.R.)FDCT/016/2013/A1
文摘In this paper, we show a backwards uniqueness theorem of the mean curvature flow with bounded second fundamental forms in arbitrary codimension.
基金The National High Technology Research and Development Program of China (863 Program) (No.2008AA01Z227)the Cultivatable Fund of the Key Scientific and Technical Innovation Project of Ministry of Education of China (No.706028)
文摘In order to enhance the accuracy and reliability of wireless location under non-line-of-sight （NLOS） environments,a novel neural network （NN） location approach using the digital broadcasting signals is presented. By the learning ability of the NN and the closely approximate unknown function to any degree of desired accuracy,the input-output mapping relationship between coordinates and the measurement data of time of arrival （TOA） and time difference of arrival （TDOA） is established. A real-time learning algorithm based on the extended Kalman filter （EKF） is used to train the multilayer perceptron （MLP） network by treating the linkweights of a network as the states of the nonlinear dynamic system. Since the EKF-based learning algorithm approximately gives the minimum variance estimate of the linkweights,the convergence is improved in comparison with the backwards error propagation （BP） algorithm. Numerical results illustrate thatthe proposedalgorithmcanachieve enhanced accuracy,and the performance ofthe algorithmis betterthanthat of the BP-based NN algorithm and the least squares （LS） algorithm in the NLOS environments. Moreover,this location method does not depend on a particular distribution of the NLOS error and does not need line-of-sight （ LOS ） or NLOS identification.
基金the National Natural Science Foundation of China under Grant No.60574016
文摘The infinite-horizon linear quadratic regulation （LQR） problem is settled for discretetime systems with input delay. With the help of an autoregressive moving average （ARMA） innovation model, solutions to the underlying problem are obtained. The design of the optimal control law involves in resolving one polynomial equation and one spectral factorization. The latter is the major obstacle of the present problem, and the reorganized innovation approach is used to clear it up. The calculation of spectral factorization finally comes down to solving two Riccati equations with the same dimension as the original systems.
