预测性流程监控(predictive process monitoring,PPM)是流程挖掘中的关键任务,旨在基于当前事件日志预测未来流程行为。然而,现有的PPM方法大多集中在对单个流程实例的短期预测,例如下一个活动预测、剩余处理时间预测等,预测范围有限且...预测性流程监控(predictive process monitoring,PPM)是流程挖掘中的关键任务,旨在基于当前事件日志预测未来流程行为。然而,现有的PPM方法大多集中在对单个流程实例的短期预测,例如下一个活动预测、剩余处理时间预测等,预测范围有限且缺乏对流程演变的全局视角,从而无法提供流程模型在较长时间范围内的演变趋势。因此,提出了一种基于时间序列分析的过程模型预测(PMF)方法,将原始事件日志转换为多维时间序列数据,系统性地捕捉流程中所有活动对(直接后继关系)在时间上的频率演变。在考虑直接后继关系之间的相互影响下,预测出未来直接跟随图,从而实现对整个过程模型的长时间范围预测。实验结果表明,该方法在多个真实流程日志上均优于传统时序分析方法,在预测准确性和稳定性方面表现突出,具备良好的应用前景。展开更多
The numerical simulation model for predicting fast filling process of 70 MPa type Ⅲ(with metal liner) hydrogen vehicle cylinder was presented,which has considered turbulence,real gas effect and solid heat transfer is...The numerical simulation model for predicting fast filling process of 70 MPa type Ⅲ(with metal liner) hydrogen vehicle cylinder was presented,which has considered turbulence,real gas effect and solid heat transfer issues.Through the numerical analysis method,the temperature distributions of the gas within the solid walls were revealed; adiabatic filling was studied to evaluate the heat dissipation during the filling; the influences of various filling conditions on temperature rise were analyzed in detail.Finally,cold filling was proposed to evaluate the effect on temperature rise and SoC(state of charge) within the cylinder.The hydrogen pre-cooling was proved to be an effective solution to reduce maximum temperature and acquire higher SoC during the filling process.展开更多
The temperature distributions of a prestressed concrete box girder bridge under the effect of cold wave processes were analyzed. The distributions were found different from those under the effect of solar radiation or...The temperature distributions of a prestressed concrete box girder bridge under the effect of cold wave processes were analyzed. The distributions were found different from those under the effect of solar radiation or nighttime radiation cooling and should not be simplified as one dimensional. A temperature predicting model that can accurately predict temperatures over the cross section of the concrete box girder was developed. On the basis of the analytical model, a two-dimensional temperature gradient model was proposed and a parametric study that considered meteorological factors was performed. The results of sensitivity analysis show that the cold wave with shorter duration and more severe temperature drop may cause more unfavorable influences on the concrete box girder bridge. Finally, the unrestrained linear curvatures, self-equilibrating stresses and bending stresses when considering the frame action of the cross section, were derived from the proposed temperature gradient model and current code provisions, respectively. Then, a comparison was made between the value calculated against proposed model and several current specifications. The results show that the cold wave may cause more unfavorable effect on the concrete box girder bridge, especially on the large concrete box girder bridge. Therefore, it is necessary to consider the thermal effect caused by cold wave during the design stage.展开更多
In order to obtain accurate prediction model and compensate for the influence of model mismatch on the control performance of the system and avoid solving nonlinear programming problem,an adaptive fuzzy predictive fun...In order to obtain accurate prediction model and compensate for the influence of model mismatch on the control performance of the system and avoid solving nonlinear programming problem,an adaptive fuzzy predictive functional control(AFPFC) scheme for multivariable nonlinear systems was proposed.Firstly,multivariable nonlinear systems were described based on Takagi-Sugeno(T-S) fuzzy models;assuming that the antecedent parameters of T-S models were kept,the consequent parameters were identified on-line by using the weighted recursive least square(WRLS) method.Secondly,the identified T-S models were linearized to be time-varying state space model at each sampling instant.Finally,by using linear predictive control technique the analysis solution of the optimal control law of AFPFC was established.The application results for pH neutralization process show that the absolute error between the identified T-S model output and the process output is smaller than 0.015;the tracking ability of the proposed AFPFC is superior to that of non-AFPFC(NAFPFC) for pH process without disturbances,the overshoot of the effluent pH value of AFPFC with disturbances is decreased by 50% compared with that of NAFPFC;when the process parameters of AFPFC vary with time the integrated absolute error(IAE) performance index still retains to be less than 200 compared with that of NAFPFC.展开更多
Gaussian process(GP)has fewer parameters,simple model and output of probabilistic sense,when compared with the methods such as support vector machines.Selection of the hyper-parameters is critical to the performance o...Gaussian process(GP)has fewer parameters,simple model and output of probabilistic sense,when compared with the methods such as support vector machines.Selection of the hyper-parameters is critical to the performance of Gaussian process model.However,the common-used algorithm has the disadvantages of difficult determination of iteration steps,over-dependence of optimization effect on initial values,and easily falling into local optimum.To solve this problem,a method combining the Gaussian process with memetic algorithm was proposed.Based on this method,memetic algorithm was used to search the optimal hyper parameters of Gaussian process regression(GPR)model in the training process and form MA-GPR algorithms,and then the model was used to predict and test the results.When used in the marine long-range precision strike system(LPSS)battle effectiveness evaluation,the proposed MA-GPR model significantly improved the prediction accuracy,compared with the conjugate gradient method and the genetic algorithm optimization process.展开更多
文摘预测性流程监控(predictive process monitoring,PPM)是流程挖掘中的关键任务,旨在基于当前事件日志预测未来流程行为。然而,现有的PPM方法大多集中在对单个流程实例的短期预测,例如下一个活动预测、剩余处理时间预测等,预测范围有限且缺乏对流程演变的全局视角,从而无法提供流程模型在较长时间范围内的演变趋势。因此,提出了一种基于时间序列分析的过程模型预测(PMF)方法,将原始事件日志转换为多维时间序列数据,系统性地捕捉流程中所有活动对(直接后继关系)在时间上的频率演变。在考虑直接后继关系之间的相互影响下,预测出未来直接跟随图,从而实现对整个过程模型的长时间范围预测。实验结果表明,该方法在多个真实流程日志上均优于传统时序分析方法,在预测准确性和稳定性方面表现突出,具备良好的应用前景。
基金support of Institute of Beijing Aeronautic and Astronautic Testing Technology in the experiments of hydrogen fast filling process under 70 MPa
文摘The numerical simulation model for predicting fast filling process of 70 MPa type Ⅲ(with metal liner) hydrogen vehicle cylinder was presented,which has considered turbulence,real gas effect and solid heat transfer issues.Through the numerical analysis method,the temperature distributions of the gas within the solid walls were revealed; adiabatic filling was studied to evaluate the heat dissipation during the filling; the influences of various filling conditions on temperature rise were analyzed in detail.Finally,cold filling was proposed to evaluate the effect on temperature rise and SoC(state of charge) within the cylinder.The hydrogen pre-cooling was proved to be an effective solution to reduce maximum temperature and acquire higher SoC during the filling process.
基金Project(08Y60) supported by the Traffic Science’s Research Planning of Jiangsu Province,China
文摘The temperature distributions of a prestressed concrete box girder bridge under the effect of cold wave processes were analyzed. The distributions were found different from those under the effect of solar radiation or nighttime radiation cooling and should not be simplified as one dimensional. A temperature predicting model that can accurately predict temperatures over the cross section of the concrete box girder was developed. On the basis of the analytical model, a two-dimensional temperature gradient model was proposed and a parametric study that considered meteorological factors was performed. The results of sensitivity analysis show that the cold wave with shorter duration and more severe temperature drop may cause more unfavorable influences on the concrete box girder bridge. Finally, the unrestrained linear curvatures, self-equilibrating stresses and bending stresses when considering the frame action of the cross section, were derived from the proposed temperature gradient model and current code provisions, respectively. Then, a comparison was made between the value calculated against proposed model and several current specifications. The results show that the cold wave may cause more unfavorable effect on the concrete box girder bridge, especially on the large concrete box girder bridge. Therefore, it is necessary to consider the thermal effect caused by cold wave during the design stage.
基金Project(2007AA04Z162) supported by the National High-Tech Research and Development Program of ChinaProjects(2006T089, 2009T062) supported by the University Innovation Team in the Educational Department of Liaoning Province, China
文摘In order to obtain accurate prediction model and compensate for the influence of model mismatch on the control performance of the system and avoid solving nonlinear programming problem,an adaptive fuzzy predictive functional control(AFPFC) scheme for multivariable nonlinear systems was proposed.Firstly,multivariable nonlinear systems were described based on Takagi-Sugeno(T-S) fuzzy models;assuming that the antecedent parameters of T-S models were kept,the consequent parameters were identified on-line by using the weighted recursive least square(WRLS) method.Secondly,the identified T-S models were linearized to be time-varying state space model at each sampling instant.Finally,by using linear predictive control technique the analysis solution of the optimal control law of AFPFC was established.The application results for pH neutralization process show that the absolute error between the identified T-S model output and the process output is smaller than 0.015;the tracking ability of the proposed AFPFC is superior to that of non-AFPFC(NAFPFC) for pH process without disturbances,the overshoot of the effluent pH value of AFPFC with disturbances is decreased by 50% compared with that of NAFPFC;when the process parameters of AFPFC vary with time the integrated absolute error(IAE) performance index still retains to be less than 200 compared with that of NAFPFC.
基金Project(513300303)supported by the General Armament Department,China
文摘Gaussian process(GP)has fewer parameters,simple model and output of probabilistic sense,when compared with the methods such as support vector machines.Selection of the hyper-parameters is critical to the performance of Gaussian process model.However,the common-used algorithm has the disadvantages of difficult determination of iteration steps,over-dependence of optimization effect on initial values,and easily falling into local optimum.To solve this problem,a method combining the Gaussian process with memetic algorithm was proposed.Based on this method,memetic algorithm was used to search the optimal hyper parameters of Gaussian process regression(GPR)model in the training process and form MA-GPR algorithms,and then the model was used to predict and test the results.When used in the marine long-range precision strike system(LPSS)battle effectiveness evaluation,the proposed MA-GPR model significantly improved the prediction accuracy,compared with the conjugate gradient method and the genetic algorithm optimization process.
