First,the state space tree method for finding communication network overall re-liability is presented.It directly generates one disjoint tree multilevel polynomial of a networkgraph.Its advantages are smaller computat...First,the state space tree method for finding communication network overall re-liability is presented.It directly generates one disjoint tree multilevel polynomial of a networkgraph.Its advantages are smaller computational effort(its computing time complexity is O(en_l),where e is the number of edges and n_l is the number of leaves)and shorter resulting expression.Second,based on it an exact decomposition algorithm for finding communication network overallreliability is presented by applying the hypergraph theory.If we use it to carry out the m-timedecomposition of a network graph,the communication network scale which can be analyzed by acomputer can be extended to m-fold.展开更多
通过在快速扩展随机树(rapidly-exploring random tree)算法的基础上融入状态-时间空间(state-timespace)的思想,使改进后的算法能够有效地处理动态环境中的航迹规划问题。仿真试验首先采用四元素法建立航天飞行器的六自由度动力学模型...通过在快速扩展随机树(rapidly-exploring random tree)算法的基础上融入状态-时间空间(state-timespace)的思想,使改进后的算法能够有效地处理动态环境中的航迹规划问题。仿真试验首先采用四元素法建立航天飞行器的六自由度动力学模型,在三维空间中验证该算法搜索高维空间的能力。其次运用改进的算法在动态环境中进行航迹规划试验,证明了该算法的有效性。展开更多
文摘First,the state space tree method for finding communication network overall re-liability is presented.It directly generates one disjoint tree multilevel polynomial of a networkgraph.Its advantages are smaller computational effort(its computing time complexity is O(en_l),where e is the number of edges and n_l is the number of leaves)and shorter resulting expression.Second,based on it an exact decomposition algorithm for finding communication network overallreliability is presented by applying the hypergraph theory.If we use it to carry out the m-timedecomposition of a network graph,the communication network scale which can be analyzed by acomputer can be extended to m-fold.
文摘通过在快速扩展随机树(rapidly-exploring random tree)算法的基础上融入状态-时间空间(state-timespace)的思想,使改进后的算法能够有效地处理动态环境中的航迹规划问题。仿真试验首先采用四元素法建立航天飞行器的六自由度动力学模型,在三维空间中验证该算法搜索高维空间的能力。其次运用改进的算法在动态环境中进行航迹规划试验,证明了该算法的有效性。
