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混成时空Petri网的CPS实时事件模型 被引量:3
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作者 谭朋柳 汪亚亚 朱明 《传感器与微系统》 CSCD 2016年第10期32-35,共4页
在分析网络物理系统(CPS)特点的基础上,提出了一种新的CPS体系结构,并对事件进行形式化定义。提出了一种新的CPS物理实体的形式化建模方法。在Petri网的基础上引入时空因素和连续变量,构造了混成时空Petri网(HSPN)模型,使其不仅能够描... 在分析网络物理系统(CPS)特点的基础上,提出了一种新的CPS体系结构,并对事件进行形式化定义。提出了一种新的CPS物理实体的形式化建模方法。在Petri网的基础上引入时空因素和连续变量,构造了混成时空Petri网(HSPN)模型,使其不仅能够描述物理实体逻辑和时间层次的行为,而且能够描述物理实体位置变迁所引起的状态变化。将其应用于实时事件CPS模型设计,以医疗控制系统为例,分析建模方法的可行性。 展开更多
关键词 混成时空Petri网(HSPN) 网络物理系统(CPS) 实时事件模型 体系结构
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The IOCAS intermediate coupled model(IOCAS ICM) and its real-time predictions of the 2015–2016 El Nio event 被引量:21
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作者 Rong-Hua Zhang 《Science Bulletin》 SCIE EI CAS CSCD 2016年第13期1061-1070,共10页
The tropical Pacific is currently experiencing an El Nifio event. Various coupled models with different degrees of complexity have been used to make real-time E1 Nifio predictions, but large uncertainties exist in the... The tropical Pacific is currently experiencing an El Nifio event. Various coupled models with different degrees of complexity have been used to make real-time E1 Nifio predictions, but large uncertainties exist in the inten- sity forecast and are strongly model dependent. An intermediate coupled model (ICM) is used at the Institute of Oceanology, Chinese Academy of Sciences (IOCAS), named the IOCAS ICM, to predict the sea surface temper- ature (SST) evolution in the tropical Pacific during the 2015-2016 E! Nifio event. One unique feature of the IOCAS ICM is the way in which the temperature of subsurface water entrained in the mixed layer (Te) is parameterized. Observed SST anomalies are only field that is utilized to initialize the coupled prediction using the IOCAS ICM. Examples are given of the model's ability to predict the SST conditions in a real-time manner. As is commonly evident in E1 Nifio- Southern Oscillation predictions using coupled models, large discrepancies occur between the observed and pre- dicted SST anomalies in spring 2015. Starting from early summer 2015, the model can realistically predict warming conditions. Thereafter, good predictions can be made through the summer and fall seasons of 2015. A transition to normal and cold conditions is predictecl to occur in rote spring 2016. Comparisons with other model predictions are made and factors influencing the prediction performance of the IOCAS ICM are also discussed. 展开更多
关键词 The 2015 E1 Nifio event IOCAS ICM Real-time prediction Model performance and improvement Air-sea interactions
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