In order to study the temporal variations of correlations between two time series,a running correlation coefficient(RCC)could be used.An RCC is calculated for a given time window,and the window is then moved sequentia...In order to study the temporal variations of correlations between two time series,a running correlation coefficient(RCC)could be used.An RCC is calculated for a given time window,and the window is then moved sequentially through time.The current calculation method for RCCs is based on the general definition of the Pearson product-moment correlation coefficient,calculated with the data within the time window,which we call the local running correlation coefficient(LRCC).The LRCC is calculated via the two anomalies corresponding to the two local means,meanwhile,the local means also vary.It is cleared up that the LRCC reflects only the correlation between the two anomalies within the time window but fails to exhibit the contributions of the two varying means.To address this problem,two unchanged means obtained from all available data are adopted to calculate an RCC,which is called the synthetic running correlation coefficient(SRCC).When the anomaly variations are dominant,the two RCCs are similar.However,when the variations of the means are dominant,the difference between the two RCCs becomes obvious.The SRCC reflects the correlations of both the anomaly variations and the variations of the means.Therefore,the SRCCs from different time points are intercomparable.A criterion for the superiority of the RCC algorithm is that the average value of the RCC should be close to the global correlation coefficient calculated using all data.The SRCC always meets this criterion,while the LRCC sometimes fails.Therefore,the SRCC is better than the LRCC for running correlations.We suggest using the SRCC to calculate the RCCs.展开更多
Environmental impact evaluation system boundary of high-speed railway was defined based on the total life cycle theory,and the index system to evaluate the environmental impact of high-speed railway was established wi...Environmental impact evaluation system boundary of high-speed railway was defined based on the total life cycle theory,and the index system to evaluate the environmental impact of high-speed railway was established with the fuzzy analytic hierarchy method,and the matter-element evaluation model was established on the basis of the extension theory.By calculating its comprehensive interrelatedness,the evaluation rank of environment impacts of high-speed railway was determined.The numerical example shows that the model has vast prospect,which can not only expand the application areas of extension theory,but also change the traditional evaluation methods and provide new ideas and means for environmental impact evaluation of high-speed railway.展开更多
It has been shown in recent economic and statistical studies that combining forecasts may produce more accurate forecasts than individual ones. However, the literature on combining forecasts has almost exclusively foc...It has been shown in recent economic and statistical studies that combining forecasts may produce more accurate forecasts than individual ones. However, the literature on combining forecasts has almost exclusively focused on linear combining forecasts. In this paper, a new nonlinear combination forecasting method based on fuzzy inference system is present to overcome the difficulties and drawbacks in linear combination modeling of non-stationary time series. Furthermore, the optimization algorithm based on a hierarchical structure of learning automata is used to identify the parameters of the fuzzy system. Experiment results related to numerical examples demonstrate that the new technique has excellent identification performances and forecasting accuracy superior to other existing linear combining forecasts.展开更多
The formation and growth of cracks in concrete dams are mainly induced by hydrostatic and temperature loads.As cracks es-pecially unstable cracks are of great danger to the safety of dams,it is critical to avoid extre...The formation and growth of cracks in concrete dams are mainly induced by hydrostatic and temperature loads.As cracks es-pecially unstable cracks are of great danger to the safety of dams,it is critical to avoid extremely adverse load combinations during the dam operations to achieve the stability of cracks.Conventionally,the adverse load combinations have to be deter-mined empirically by experts based on specific dam site conditions.Therefore,it is attractive to apply quantitative instead of empirical methods to identify the adverse loading conditions.In this study,we employ an adaptive neuro-fuzzy inference sys-tem(ANFIS) to Chencun concrete dam.The ANFIS is able to help us build a relationship between the model inputs(reservoir water level and air temperature) and the model output(crack opening displacement).Based on this relationship,the rules of the adverse load combinations to the crack are generated directly from the monitoring data.The accuracy of the trained ANFIS is proved by comparing the modeling results and the monitoring data.Our work demonstrates that the ANFIS is a useful ap-proach for accurately recognizing the rules of the adverse load combinations that can be used in the knowledge base of dam safety expert system.展开更多
Flexibility plays an important part in the application of the workflow management system and has become one of the major research hotspots in this field recently. When adapting a workflow process definition to specifi...Flexibility plays an important part in the application of the workflow management system and has become one of the major research hotspots in this field recently. When adapting a workflow process definition to specific needs or changing the structure of the workflow process as a result of evolutionary change, coarse-grained reuse of work- flow is of significance to the reduction of the work effort, modeling system and enhancing the reliability of their work. Based on decomposition of workflow tasks and teamwork, this paper proposes an approach to describing interoperability behavior between roles in teamwork by using activity-pattern. In activity-pattern, abstract mechanisms of activity specialization and activity aggregation are presented, enabling reuse of workflow by means of reuse of interoperability behavior between roles. The experimental system shows that our approach presented is feasible.展开更多
基金supported by the Key Program of the National Natural Science Foundation of China (No. 41330960)the Global Change Research Program of China (No. 2015CB953900)
文摘In order to study the temporal variations of correlations between two time series,a running correlation coefficient(RCC)could be used.An RCC is calculated for a given time window,and the window is then moved sequentially through time.The current calculation method for RCCs is based on the general definition of the Pearson product-moment correlation coefficient,calculated with the data within the time window,which we call the local running correlation coefficient(LRCC).The LRCC is calculated via the two anomalies corresponding to the two local means,meanwhile,the local means also vary.It is cleared up that the LRCC reflects only the correlation between the two anomalies within the time window but fails to exhibit the contributions of the two varying means.To address this problem,two unchanged means obtained from all available data are adopted to calculate an RCC,which is called the synthetic running correlation coefficient(SRCC).When the anomaly variations are dominant,the two RCCs are similar.However,when the variations of the means are dominant,the difference between the two RCCs becomes obvious.The SRCC reflects the correlations of both the anomaly variations and the variations of the means.Therefore,the SRCCs from different time points are intercomparable.A criterion for the superiority of the RCC algorithm is that the average value of the RCC should be close to the global correlation coefficient calculated using all data.The SRCC always meets this criterion,while the LRCC sometimes fails.Therefore,the SRCC is better than the LRCC for running correlations.We suggest using the SRCC to calculate the RCCs.
基金Project(2011QNZT062)supported by the Fundamental Research Funds for Central Universities of China
文摘Environmental impact evaluation system boundary of high-speed railway was defined based on the total life cycle theory,and the index system to evaluate the environmental impact of high-speed railway was established with the fuzzy analytic hierarchy method,and the matter-element evaluation model was established on the basis of the extension theory.By calculating its comprehensive interrelatedness,the evaluation rank of environment impacts of high-speed railway was determined.The numerical example shows that the model has vast prospect,which can not only expand the application areas of extension theory,but also change the traditional evaluation methods and provide new ideas and means for environmental impact evaluation of high-speed railway.
基金Funded by the Excellent Young Teachers of MOE (350) and Chongqing Education Committee Foundation
文摘It has been shown in recent economic and statistical studies that combining forecasts may produce more accurate forecasts than individual ones. However, the literature on combining forecasts has almost exclusively focused on linear combining forecasts. In this paper, a new nonlinear combination forecasting method based on fuzzy inference system is present to overcome the difficulties and drawbacks in linear combination modeling of non-stationary time series. Furthermore, the optimization algorithm based on a hierarchical structure of learning automata is used to identify the parameters of the fuzzy system. Experiment results related to numerical examples demonstrate that the new technique has excellent identification performances and forecasting accuracy superior to other existing linear combining forecasts.
基金supported by the National Natural Science Foundation of China (Grant Nos.50909041 and 41072217)
文摘The formation and growth of cracks in concrete dams are mainly induced by hydrostatic and temperature loads.As cracks es-pecially unstable cracks are of great danger to the safety of dams,it is critical to avoid extremely adverse load combinations during the dam operations to achieve the stability of cracks.Conventionally,the adverse load combinations have to be deter-mined empirically by experts based on specific dam site conditions.Therefore,it is attractive to apply quantitative instead of empirical methods to identify the adverse loading conditions.In this study,we employ an adaptive neuro-fuzzy inference sys-tem(ANFIS) to Chencun concrete dam.The ANFIS is able to help us build a relationship between the model inputs(reservoir water level and air temperature) and the model output(crack opening displacement).Based on this relationship,the rules of the adverse load combinations to the crack are generated directly from the monitoring data.The accuracy of the trained ANFIS is proved by comparing the modeling results and the monitoring data.Our work demonstrates that the ANFIS is a useful ap-proach for accurately recognizing the rules of the adverse load combinations that can be used in the knowledge base of dam safety expert system.
基金This research is supported by National Natural Science Foundation of China （60574028） the Key Projects of Natural Science Foundation of Edtication Department of Anhui Province of China （2006kj016A, 2005kj065）
文摘Flexibility plays an important part in the application of the workflow management system and has become one of the major research hotspots in this field recently. When adapting a workflow process definition to specific needs or changing the structure of the workflow process as a result of evolutionary change, coarse-grained reuse of work- flow is of significance to the reduction of the work effort, modeling system and enhancing the reliability of their work. Based on decomposition of workflow tasks and teamwork, this paper proposes an approach to describing interoperability behavior between roles in teamwork by using activity-pattern. In activity-pattern, abstract mechanisms of activity specialization and activity aggregation are presented, enabling reuse of workflow by means of reuse of interoperability behavior between roles. The experimental system shows that our approach presented is feasible.
