Let G be a fc-regular connected vertex transitive graph. If G is not maximal restricted edge connected, then G has a (k- 1)-factor with components isomorphic to the same vertex transitive graph of order between k and ...Let G be a fc-regular connected vertex transitive graph. If G is not maximal restricted edge connected, then G has a (k- 1)-factor with components isomorphic to the same vertex transitive graph of order between k and 2k-3. This observation strenghen to some extent the corresponding result obtained by Watkins, which said that fc-regular vertex transitive graph G has a factor with components isomorphic to a vertex transitive graphs if G is not k connected.展开更多
Regularization inversion uses constraints and a regularization factor to solve ill- posed inversion problems in geophysics. The choice of the regularization factor and of the initial model is critical in regularizatio...Regularization inversion uses constraints and a regularization factor to solve ill- posed inversion problems in geophysics. The choice of the regularization factor and of the initial model is critical in regularization inversion. To deal with these problems, we propose a multiobjective particle swarm inversion （MOPSOI） algorithm to simultaneously minimize the data misfit and model constraints, and obtain a multiobjective inversion solution set without the gradient information of the objective function and the regularization factor. We then choose the optimum solution from the solution set based on the trade-off between data misfit and constraints that substitute for the regularization factor. The inversion of synthetic two-dimensional magnetic data suggests that the MOPSOI algorithm can obtain as many feasible solutions as possible; thus, deeper insights of the inversion process can be gained and more reasonable solutions can be obtained by balancing the data misfit and constraints. The proposed MOPSOI algorithm can deal with the problems of choosing the right regularization factor and the initial model.展开更多
基金Supported by NNSF of China(10271105) Doctoral Foundation of Zhangzhou Normal College.
文摘Let G be a fc-regular connected vertex transitive graph. If G is not maximal restricted edge connected, then G has a (k- 1)-factor with components isomorphic to the same vertex transitive graph of order between k and 2k-3. This observation strenghen to some extent the corresponding result obtained by Watkins, which said that fc-regular vertex transitive graph G has a factor with components isomorphic to a vertex transitive graphs if G is not k connected.
基金supported by the Natural Science Foundation of China(No.61273179)Department of Education,Science and Technology Research Project of Hubei Province of China(No.D20131206,No.20141304)
文摘Regularization inversion uses constraints and a regularization factor to solve ill- posed inversion problems in geophysics. The choice of the regularization factor and of the initial model is critical in regularization inversion. To deal with these problems, we propose a multiobjective particle swarm inversion （MOPSOI） algorithm to simultaneously minimize the data misfit and model constraints, and obtain a multiobjective inversion solution set without the gradient information of the objective function and the regularization factor. We then choose the optimum solution from the solution set based on the trade-off between data misfit and constraints that substitute for the regularization factor. The inversion of synthetic two-dimensional magnetic data suggests that the MOPSOI algorithm can obtain as many feasible solutions as possible; thus, deeper insights of the inversion process can be gained and more reasonable solutions can be obtained by balancing the data misfit and constraints. The proposed MOPSOI algorithm can deal with the problems of choosing the right regularization factor and the initial model.
