Stress field plays a key role in geodynamics. In this study, an algorithm to determine the stress tensor and its confidence range from focal mechanism data by using grid search method was proposed. The experiment uses...Stress field plays a key role in geodynamics. In this study, an algorithm to determine the stress tensor and its confidence range from focal mechanism data by using grid search method was proposed. The experiment uses artificial focal mechanism data which were generated by extensional, compression and strike-slip stress regime and different level of noise, shows that the precision of the estimated stress tensor based on this algorithm is greatly improved compared with traditional algorithms. This algorithm has three advantages：（1） The global optimal solution of the stress tensor is determined by fine grid search of 1o×1o×1o×0.01 and local minimum value is avoided; （2） precision of focal mechanism data can be considered, i.e., different weight of the focal mechanism data contributes differently to the process of determining stress tensor; （3） the confidence range of the determined stress tensor can be obtained by using F-test. We apply this algorithm in the boundary zone of China, Vietnam and Laos, and obtain the stress field with SSE-NNW compressive stress direction and NEE-SWW extensional stress direction. The stress ratio is 0.6, which shows that the eigen values of the stress tensor are nearly in arithmetic sequence. The stress field in this region is consistent with the left-lateral strike slip of the Dienbien-Lauangphrabang arc fault. The result will be helpful in studying the geological dynamic process in this region.展开更多
Artificial bee colony(ABC) is one of the most popular swarm intelligence optimization algorithms which have been widely used in numerical optimization and engineering applications. However, there are still deficiencie...Artificial bee colony(ABC) is one of the most popular swarm intelligence optimization algorithms which have been widely used in numerical optimization and engineering applications. However, there are still deficiencies in ABC regarding its local search ability and global search efficiency. Aiming at these deficiencies,an ABC variant named hybrid ABC(HABC) algorithm is proposed.Firstly, the variable neighborhood search factor is added to the solution search equation, which can enhance the local search ability and increase the population diversity. Secondly, inspired by the neuroscience investigation of real honeybees, the memory mechanism is put forward, which assumes the artificial bees can remember their past successful experiences and further guide the subsequent foraging behavior. The proposed memory mechanism is used to improve the global search efficiency. Finally, the results of comparison on a set of ten benchmark functions demonstrate the superiority of HABC.展开更多
Abstract. Conjugate gradient methods are very important methods for unconstrainedoptimization, especially for large scale problems. In this paper, we propose a new conjugategradient method, in which the technique of n...Abstract. Conjugate gradient methods are very important methods for unconstrainedoptimization, especially for large scale problems. In this paper, we propose a new conjugategradient method, in which the technique of nonmonotone line search is used. Under mildassumptions, we prove the global convergence of the method. Some numerical results arealso presented.展开更多
基金supported by Natural Science Foundation of China(No.41674055)the Earthquake Science and Technology Spark Plan in Hebei Province(DZ20140101002)
文摘Stress field plays a key role in geodynamics. In this study, an algorithm to determine the stress tensor and its confidence range from focal mechanism data by using grid search method was proposed. The experiment uses artificial focal mechanism data which were generated by extensional, compression and strike-slip stress regime and different level of noise, shows that the precision of the estimated stress tensor based on this algorithm is greatly improved compared with traditional algorithms. This algorithm has three advantages：（1） The global optimal solution of the stress tensor is determined by fine grid search of 1o×1o×1o×0.01 and local minimum value is avoided; （2） precision of focal mechanism data can be considered, i.e., different weight of the focal mechanism data contributes differently to the process of determining stress tensor; （3） the confidence range of the determined stress tensor can be obtained by using F-test. We apply this algorithm in the boundary zone of China, Vietnam and Laos, and obtain the stress field with SSE-NNW compressive stress direction and NEE-SWW extensional stress direction. The stress ratio is 0.6, which shows that the eigen values of the stress tensor are nearly in arithmetic sequence. The stress field in this region is consistent with the left-lateral strike slip of the Dienbien-Lauangphrabang arc fault. The result will be helpful in studying the geological dynamic process in this region.
基金supported by the National Natural Science Foundation of China(7177121671701209)
文摘Artificial bee colony(ABC) is one of the most popular swarm intelligence optimization algorithms which have been widely used in numerical optimization and engineering applications. However, there are still deficiencies in ABC regarding its local search ability and global search efficiency. Aiming at these deficiencies,an ABC variant named hybrid ABC(HABC) algorithm is proposed.Firstly, the variable neighborhood search factor is added to the solution search equation, which can enhance the local search ability and increase the population diversity. Secondly, inspired by the neuroscience investigation of real honeybees, the memory mechanism is put forward, which assumes the artificial bees can remember their past successful experiences and further guide the subsequent foraging behavior. The proposed memory mechanism is used to improve the global search efficiency. Finally, the results of comparison on a set of ten benchmark functions demonstrate the superiority of HABC.
基金the National Natural Science Foundation of China(19801033,10171104).
文摘Abstract. Conjugate gradient methods are very important methods for unconstrainedoptimization, especially for large scale problems. In this paper, we propose a new conjugategradient method, in which the technique of nonmonotone line search is used. Under mildassumptions, we prove the global convergence of the method. Some numerical results arealso presented.
