The probabilistic real-time automaton （PRTA） is a representation of dynamic processes arising in the sciences and industry. Currently, the induction of automata is divided into two steps： the creation of the prefix...The probabilistic real-time automaton （PRTA） is a representation of dynamic processes arising in the sciences and industry. Currently, the induction of automata is divided into two steps： the creation of the prefix tree acceptor （PTA） and the merge procedure based on clustering of the states. These two steps can be very time intensive when a PRTA is to be induced for massive or even unbounded datasets. The latter one can be efficiently processed, as there exist scalable online clustering algorithms. However, the creation of the PTA still can be very time consuming. To overcome this problem, we propose a genuine online PRTA induction approach that incorporates new instances by first collapsing them and then using a maximum frequent pattern based clustering. The approach is tested against a predefined synthetic automaton and real world datasets, for which the approach is scalable and stable. Moreover, we present a broad evaluation on a real world disease group dataset that shows the applicability of such a model to the analysis of medical processes.展开更多
The inductances in d-q axis have an important influence on the behavior of PMSM （PM （permanent-magnet） synchronous machines）. Their calculation is fundamental not only to evaluate the performance such as torque an...The inductances in d-q axis have an important influence on the behavior of PMSM （PM （permanent-magnet） synchronous machines）. Their calculation is fundamental not only to evaluate the performance such as torque and field weakening capability but also to design the control system to maximize performance and power factor. This paper presents a study of inductance in the d-q axis for buried （i.e., IPMSM （interior） PM Synchronous Machines）. This study is achieved using 2-D （two-dimensional） FEM （finite-element method） and Park＇s transformation.展开更多
文摘The probabilistic real-time automaton （PRTA） is a representation of dynamic processes arising in the sciences and industry. Currently, the induction of automata is divided into two steps： the creation of the prefix tree acceptor （PTA） and the merge procedure based on clustering of the states. These two steps can be very time intensive when a PRTA is to be induced for massive or even unbounded datasets. The latter one can be efficiently processed, as there exist scalable online clustering algorithms. However, the creation of the PTA still can be very time consuming. To overcome this problem, we propose a genuine online PRTA induction approach that incorporates new instances by first collapsing them and then using a maximum frequent pattern based clustering. The approach is tested against a predefined synthetic automaton and real world datasets, for which the approach is scalable and stable. Moreover, we present a broad evaluation on a real world disease group dataset that shows the applicability of such a model to the analysis of medical processes.
文摘The inductances in d-q axis have an important influence on the behavior of PMSM （PM （permanent-magnet） synchronous machines）. Their calculation is fundamental not only to evaluate the performance such as torque and field weakening capability but also to design the control system to maximize performance and power factor. This paper presents a study of inductance in the d-q axis for buried （i.e., IPMSM （interior） PM Synchronous Machines）. This study is achieved using 2-D （two-dimensional） FEM （finite-element method） and Park＇s transformation.
