Based on the evaluation of advantages and disadvantages of high-precision digital time interval measuring algorithms, and combined with the principle of the typical time-difference ultrasonic flow measurement, the req...Based on the evaluation of advantages and disadvantages of high-precision digital time interval measuring algorithms, and combined with the principle of the typical time-difference ultrasonic flow measurement, the requirements for the measurement of echo time of flight put forward by the ultrasonic flow measurement are analyzed. A new high-precision time interval measurement algorithm is presented, which combines the pulse counting method with the phase delay interpolation. The pulse counting method is used to ensure a large dynamic measuring range, and a double-edge triggering counter is designed to improve the accuracy and reduce the counting quantization error. The phase delay interpolation is used to reduce the quantization error of pulse counting for further improving the time measurement resolution. Test data show that the systexn for the measurement of the ultrasonic echo time of flight based on this algorithm and implemented on an Field Programmable Gate Army（FleA） needs a relatively short time for measurement, and has a measurement error of less than 105 ps.展开更多
The authors will examine prediction of temperature daily profile using various modifications of BPTT （backpropagation through time algorithm） done by stochastic update in the artificial RCNN （recurrent neural netwo...The authors will examine prediction of temperature daily profile using various modifications of BPTT （backpropagation through time algorithm） done by stochastic update in the artificial RCNN （recurrent neural networks）. The general introduction was provided by Salvetti and Wilamowski in 1994 in order to improve probability of convergence and speed of convergence. This update method has also one another quality, its implementation is simple for arbitrary network topology. In stochastic update scenario, constant number of weights/neurons is randomly selected and updated. This is in contrast to classical ordered update, where always all weights/neurons are updated. Stochastic update is suitable to replace classical ordered update without any penalty on implementation complexity and with good chance without penalty on quality of convergence. They have provided first experiments with stochastic modification on BP （backpropagation algorithm） used for artificial FFNN （feed-forward neural network） in detail described in the article ＂Stochastic Weight Update in the Backpropagation Algorithm on Feed-Forward Neural Networks＂ presented on the conference IJCNN （International Joint Conference of Neural Networks） 2010 in Barcelona. The BPTT on RCNN uses the history of previous steps stored inside of the NN that can be used for prediction. They will describe exact implementation on the RCNN, and present experiment results on temperature prediction with recurrent neural network topology. The dataset used for temperature prediction consists of the measured temperature from the year 2000 till the end of February 2011. Dataset is split into two groups： training dataset, which is provided to network in learning phase, and testing dataset, which is unknown part of dataset to NN and used to test the ability of NN to predict the temperature and the ability of NN to generalize the model hidden in the temperature profile. The results show promising properties of stochastic weight update with toy-task data, and th展开更多
In this paper, the single machine scheduling problem with release dates and two hierarchical criteria is discussed. The first criterion is to minimize makespan, and the second criterion is to minimize stocking cost. W...In this paper, the single machine scheduling problem with release dates and two hierarchical criteria is discussed. The first criterion is to minimize makespan, and the second criterion is to minimize stocking cost. We show that this problem is strongly NP-hard. We also give an O（n^2） time algorithm for the special case that all stocking costs of jobs in unit time are 1.展开更多
A three-dimensional, nineteen-velocity(D3Q19) Lattice Boltzmann Method(LBM) model was developed to simulate the fluid flow of a laminar square jet in cross flows based on the single relaxation time algorithm. The code...A three-dimensional, nineteen-velocity(D3Q19) Lattice Boltzmann Method(LBM) model was developed to simulate the fluid flow of a laminar square jet in cross flows based on the single relaxation time algorithm. The code was validated by the mathematic solution of the Poiseuille flow in a square channel, and was further validated with a previous well studied empirical correlation for the central trajectory of a jet in cross flows. The developed LBM model was found to be able to capture the dominant vortex, i.e. the Counter-rotating Vortex Pair(CVP) and the upright wake vortex. Results show that the incoming fluid in the cross flow channel was entrained into the leeside of the jet fluid, which contributes to the blending of the jet. That the spread width of the transverse jet decreases with the velocity ratio. A layer-organized entrainment pattern was found indicating that the incoming fluid at the lower position is firstly entrained into the leeside of the jet, and followed by the incoming fluid at the upper position.展开更多
重型车辆具有重心高,装载量大,高宽比相对乘用车较大等特点,导致其侧翻稳定极限较低,极易发生侧翻事故。建立重型车辆侧翻预测模型,利用车辆实车试验数据离线辨识技术,辨识出3自由度车辆模型中的关键参数,然后利用改进后的车辆模型进行...重型车辆具有重心高,装载量大,高宽比相对乘用车较大等特点,导致其侧翻稳定极限较低,极易发生侧翻事故。建立重型车辆侧翻预测模型,利用车辆实车试验数据离线辨识技术,辨识出3自由度车辆模型中的关键参数,然后利用改进后的车辆模型进行在线侧翻危险预测及控制,实现车辆动态侧翻特性精确预测。在此基础上,将卡尔曼滤波技术融入到改进侧翻预测时间(Time to rollover,TTR)侧翻预警算法中,选取车辆的横向载荷转移率作为侧翻极限判据,根据当前车辆状态预测未来3 s车辆的侧翻危险程度,并实时计算TTR值,一旦TTR值满足侧翻条件,系统自动触发预警装置。利用侧翻预警系统车载试验平台,对侧翻预警控制系统进行验证。侧翻预警场地试验结果表明:所开发的重型车辆侧翻预警系统可以准确有效地进行车辆侧翻危险程度预警,达到预期的开发设计目标。展开更多
基金supported by the National 863 Program(No.2008AA042207)
文摘Based on the evaluation of advantages and disadvantages of high-precision digital time interval measuring algorithms, and combined with the principle of the typical time-difference ultrasonic flow measurement, the requirements for the measurement of echo time of flight put forward by the ultrasonic flow measurement are analyzed. A new high-precision time interval measurement algorithm is presented, which combines the pulse counting method with the phase delay interpolation. The pulse counting method is used to ensure a large dynamic measuring range, and a double-edge triggering counter is designed to improve the accuracy and reduce the counting quantization error. The phase delay interpolation is used to reduce the quantization error of pulse counting for further improving the time measurement resolution. Test data show that the systexn for the measurement of the ultrasonic echo time of flight based on this algorithm and implemented on an Field Programmable Gate Army（FleA） needs a relatively short time for measurement, and has a measurement error of less than 105 ps.
文摘The authors will examine prediction of temperature daily profile using various modifications of BPTT （backpropagation through time algorithm） done by stochastic update in the artificial RCNN （recurrent neural networks）. The general introduction was provided by Salvetti and Wilamowski in 1994 in order to improve probability of convergence and speed of convergence. This update method has also one another quality, its implementation is simple for arbitrary network topology. In stochastic update scenario, constant number of weights/neurons is randomly selected and updated. This is in contrast to classical ordered update, where always all weights/neurons are updated. Stochastic update is suitable to replace classical ordered update without any penalty on implementation complexity and with good chance without penalty on quality of convergence. They have provided first experiments with stochastic modification on BP （backpropagation algorithm） used for artificial FFNN （feed-forward neural network） in detail described in the article ＂Stochastic Weight Update in the Backpropagation Algorithm on Feed-Forward Neural Networks＂ presented on the conference IJCNN （International Joint Conference of Neural Networks） 2010 in Barcelona. The BPTT on RCNN uses the history of previous steps stored inside of the NN that can be used for prediction. They will describe exact implementation on the RCNN, and present experiment results on temperature prediction with recurrent neural network topology. The dataset used for temperature prediction consists of the measured temperature from the year 2000 till the end of February 2011. Dataset is split into two groups： training dataset, which is provided to network in learning phase, and testing dataset, which is unknown part of dataset to NN and used to test the ability of NN to predict the temperature and the ability of NN to generalize the model hidden in the temperature profile. The results show promising properties of stochastic weight update with toy-task data, and th
文摘In this paper, the single machine scheduling problem with release dates and two hierarchical criteria is discussed. The first criterion is to minimize makespan, and the second criterion is to minimize stocking cost. We show that this problem is strongly NP-hard. We also give an O（n^2） time algorithm for the special case that all stocking costs of jobs in unit time are 1.
基金Supported by the National Natural Science Foundation of China(51476145,51476146)
文摘A three-dimensional, nineteen-velocity(D3Q19) Lattice Boltzmann Method(LBM) model was developed to simulate the fluid flow of a laminar square jet in cross flows based on the single relaxation time algorithm. The code was validated by the mathematic solution of the Poiseuille flow in a square channel, and was further validated with a previous well studied empirical correlation for the central trajectory of a jet in cross flows. The developed LBM model was found to be able to capture the dominant vortex, i.e. the Counter-rotating Vortex Pair(CVP) and the upright wake vortex. Results show that the incoming fluid in the cross flow channel was entrained into the leeside of the jet fluid, which contributes to the blending of the jet. That the spread width of the transverse jet decreases with the velocity ratio. A layer-organized entrainment pattern was found indicating that the incoming fluid at the lower position is firstly entrained into the leeside of the jet, and followed by the incoming fluid at the upper position.
文摘重型车辆具有重心高,装载量大,高宽比相对乘用车较大等特点,导致其侧翻稳定极限较低,极易发生侧翻事故。建立重型车辆侧翻预测模型,利用车辆实车试验数据离线辨识技术,辨识出3自由度车辆模型中的关键参数,然后利用改进后的车辆模型进行在线侧翻危险预测及控制,实现车辆动态侧翻特性精确预测。在此基础上,将卡尔曼滤波技术融入到改进侧翻预测时间(Time to rollover,TTR)侧翻预警算法中,选取车辆的横向载荷转移率作为侧翻极限判据,根据当前车辆状态预测未来3 s车辆的侧翻危险程度,并实时计算TTR值,一旦TTR值满足侧翻条件,系统自动触发预警装置。利用侧翻预警系统车载试验平台,对侧翻预警控制系统进行验证。侧翻预警场地试验结果表明:所开发的重型车辆侧翻预警系统可以准确有效地进行车辆侧翻危险程度预警,达到预期的开发设计目标。
