基于组件对象模型COM的组件具有可重用性、语言独立性、自描述性等优点,将Fortran计算程序/数学模型建造成COM组件并集成到组件软件系统是一必然发展要求.COM组件拥有怎样的基本特征,如何规划、设计Fortran COM组件,CVF计算开发环境中的...基于组件对象模型COM的组件具有可重用性、语言独立性、自描述性等优点,将Fortran计算程序/数学模型建造成COM组件并集成到组件软件系统是一必然发展要求.COM组件拥有怎样的基本特征,如何规划、设计Fortran COM组件,CVF计算开发环境中的Fortran COM Server Wizard插件为创建Fortran COM组件提供了哪些方面的支持,在COM组件中能否直接使用Fortran数据类型,就这样一些Fortran编程人员所关注的基本问题进行探讨.展开更多
To make full use of the gas resource, stabilize the pipe network pressure, and obtain higher economic benefits in the iron and steel industry, the surplus gas prediction and scheduling models were proposed. Before app...To make full use of the gas resource, stabilize the pipe network pressure, and obtain higher economic benefits in the iron and steel industry, the surplus gas prediction and scheduling models were proposed. Before applying the forecasting techniques, a support vector classifier was first used to classify the data, and then the filtering was used to create separate trend and volatility sequences. After forecasting, the Markov chain transition probability matrix was introduced to adjust the residual. Simulation results using surplus gas data from an iron and steel enterprise demonstrate that the constructed SVC-HP-ENN-LSSVM-MC prediction model prediction is accurate, and that the classification accuracy is high under different conditions. Based on this, the scheduling model was constructed for surplus gas operating, and it has been used to investigate the comprehensive measures for managing the operational probabilistic risk and optimize the economic benefit at various working conditions and implementations. It has extended the concepts of traditional surplus gas dispatching systems, and provides a method for enterprises to determine optimal schedules.展开更多
文摘基于组件对象模型COM的组件具有可重用性、语言独立性、自描述性等优点,将Fortran计算程序/数学模型建造成COM组件并集成到组件软件系统是一必然发展要求.COM组件拥有怎样的基本特征,如何规划、设计Fortran COM组件,CVF计算开发环境中的Fortran COM Server Wizard插件为创建Fortran COM组件提供了哪些方面的支持,在COM组件中能否直接使用Fortran数据类型,就这样一些Fortran编程人员所关注的基本问题进行探讨.
基金Project(51204082)supported by the National Natural Science Foundation of ChinaProject(KKSY201458118)supported by the Talent Cultivation Project of Kuning University of Science and Technology,China
文摘To make full use of the gas resource, stabilize the pipe network pressure, and obtain higher economic benefits in the iron and steel industry, the surplus gas prediction and scheduling models were proposed. Before applying the forecasting techniques, a support vector classifier was first used to classify the data, and then the filtering was used to create separate trend and volatility sequences. After forecasting, the Markov chain transition probability matrix was introduced to adjust the residual. Simulation results using surplus gas data from an iron and steel enterprise demonstrate that the constructed SVC-HP-ENN-LSSVM-MC prediction model prediction is accurate, and that the classification accuracy is high under different conditions. Based on this, the scheduling model was constructed for surplus gas operating, and it has been used to investigate the comprehensive measures for managing the operational probabilistic risk and optimize the economic benefit at various working conditions and implementations. It has extended the concepts of traditional surplus gas dispatching systems, and provides a method for enterprises to determine optimal schedules.
