Local and global optimization methods are widely used in geophysical inversion but each has its own advantages and disadvantages. The combination of the two methods will make it possible to overcome their weaknesses. ...Local and global optimization methods are widely used in geophysical inversion but each has its own advantages and disadvantages. The combination of the two methods will make it possible to overcome their weaknesses. Based on the simulated annealing genetic algorithm （SAGA） and the simplex algorithm, an efficient and robust 2-D nonlinear method for seismic travel-time inversion is presented in this paper. First we do a global search over a large range by SAGA and then do a rapid local search using the simplex method. A multi-scale tomography method is adopted in order to reduce non-uniqueness. The velocity field is divided into different spatial scales and velocities at the grid nodes are taken as unknown parameters. The model is parameterized by a bi-cubic spline function. The finite-difference method is used to solve the forward problem while the hybrid method combining multi-scale SAGA and simplex algorithms is applied to the inverse problem. The algorithm has been applied to a numerical test and a travel-time perturbation test using an anomalous low-velocity body. For a practical example, it is used in the study of upper crustal velocity structure of the A＇nyemaqen suture zone at the north-east edge of the Qinghai-Tibet Plateau. The model test and practical application both prove that the method is effective and robust.展开更多
In recent years,high-tech development zones(hi-tech zones)have always occupied a very important position in the strategy of promoting China's innovative development.The combination of the"four-transform and t...In recent years,high-tech development zones(hi-tech zones)have always occupied a very important position in the strategy of promoting China's innovative development.The combination of the"four-transform and three-famous"coordinated economic development strategy pioneered by Zhejiang Province in 2015 and the coordinated economic development of high-tech zones is particularly important for modern China at a critical time for innovative economic development.In this article,based on the research on the coordination mechanism of economic activities and development of Nanchang High-tech Zone,the development course of high-tech zones in China is elaborated,the early economic models in high-tech zones of Nanchang and China are analyzed,the existing problems in the structure of economic development of high-tech zones are analyzed in depth,the main driving factors for promoting the economic development of high-tech zones are studied from the aspects of capital,space,industry,economic model,etc.,and corresponding development strategies for high-tech development zones in China are proposed.展开更多
城市作战的重要性日益凸显,城市作战路径规划也受到了更多的关注。如何在城市复杂的环境和众多危险区中寻找安全迅速的路径是非常重要的。为保障作战安全,提出了一种基于选拔科特鸟和路径缩减的不规则危险区路径规划算法。首先,结合城...城市作战的重要性日益凸显,城市作战路径规划也受到了更多的关注。如何在城市复杂的环境和众多危险区中寻找安全迅速的路径是非常重要的。为保障作战安全,提出了一种基于选拔科特鸟和路径缩减的不规则危险区路径规划算法。首先,结合城市危险区特征和受限情况以构建更符合真实战场的不规则危险区数学模型。其次,建立路径空间缩减模型对路径威胁度进行评估和量化,以剔除掉高威胁路径来降低作战风险。最后,基于选拔策略的科特鸟优化算法(COOT Bird Optimization Algorithm based on Selection Strategy,SS-COOT)结合优质个体以提高算法的寻优效率。经实验验证,该算法在结合不规则危险区的城市路径规划问题上具有搜索速度快、寻优效果好的特点。展开更多
Many isolation approaches, such as zoning search, have been proposed to preserve the diversity in the decision space of multimodal multi-objective optimization(MMO). However, these approaches allocate the same computi...Many isolation approaches, such as zoning search, have been proposed to preserve the diversity in the decision space of multimodal multi-objective optimization(MMO). However, these approaches allocate the same computing resources for subspaces with different difficulties and evolution states. In order to solve this issue, this paper proposes a dynamic resource allocation strategy(DRAS)with reinforcement learning for multimodal multi-objective optimization problems(MMOPs). In DRAS, relative contribution and improvement are utilized to define the aptitude of subspaces, which can capture the potentials of subspaces accurately. Moreover, the reinforcement learning method is used to dynamically allocate computing resources for each subspace. In addition, the proposed DRAS is applied to zoning searches. Experimental results demonstrate that DRAS can effectively assist zoning search in finding more and better distributed equivalent Pareto optimal solutions in the decision space.展开更多
基金supported by the National Natural Science Foundation of China (Grant Nos.40334040 and 40974033)the Promoting Foundation for Advanced Persons of Talent of NCWU
文摘Local and global optimization methods are widely used in geophysical inversion but each has its own advantages and disadvantages. The combination of the two methods will make it possible to overcome their weaknesses. Based on the simulated annealing genetic algorithm （SAGA） and the simplex algorithm, an efficient and robust 2-D nonlinear method for seismic travel-time inversion is presented in this paper. First we do a global search over a large range by SAGA and then do a rapid local search using the simplex method. A multi-scale tomography method is adopted in order to reduce non-uniqueness. The velocity field is divided into different spatial scales and velocities at the grid nodes are taken as unknown parameters. The model is parameterized by a bi-cubic spline function. The finite-difference method is used to solve the forward problem while the hybrid method combining multi-scale SAGA and simplex algorithms is applied to the inverse problem. The algorithm has been applied to a numerical test and a travel-time perturbation test using an anomalous low-velocity body. For a practical example, it is used in the study of upper crustal velocity structure of the A＇nyemaqen suture zone at the north-east edge of the Qinghai-Tibet Plateau. The model test and practical application both prove that the method is effective and robust.
文摘In recent years,high-tech development zones(hi-tech zones)have always occupied a very important position in the strategy of promoting China's innovative development.The combination of the"four-transform and three-famous"coordinated economic development strategy pioneered by Zhejiang Province in 2015 and the coordinated economic development of high-tech zones is particularly important for modern China at a critical time for innovative economic development.In this article,based on the research on the coordination mechanism of economic activities and development of Nanchang High-tech Zone,the development course of high-tech zones in China is elaborated,the early economic models in high-tech zones of Nanchang and China are analyzed,the existing problems in the structure of economic development of high-tech zones are analyzed in depth,the main driving factors for promoting the economic development of high-tech zones are studied from the aspects of capital,space,industry,economic model,etc.,and corresponding development strategies for high-tech development zones in China are proposed.
文摘城市作战的重要性日益凸显,城市作战路径规划也受到了更多的关注。如何在城市复杂的环境和众多危险区中寻找安全迅速的路径是非常重要的。为保障作战安全,提出了一种基于选拔科特鸟和路径缩减的不规则危险区路径规划算法。首先,结合城市危险区特征和受限情况以构建更符合真实战场的不规则危险区数学模型。其次,建立路径空间缩减模型对路径威胁度进行评估和量化,以剔除掉高威胁路径来降低作战风险。最后,基于选拔策略的科特鸟优化算法(COOT Bird Optimization Algorithm based on Selection Strategy,SS-COOT)结合优质个体以提高算法的寻优效率。经实验验证,该算法在结合不规则危险区的城市路径规划问题上具有搜索速度快、寻优效果好的特点。
文摘Many isolation approaches, such as zoning search, have been proposed to preserve the diversity in the decision space of multimodal multi-objective optimization(MMO). However, these approaches allocate the same computing resources for subspaces with different difficulties and evolution states. In order to solve this issue, this paper proposes a dynamic resource allocation strategy(DRAS)with reinforcement learning for multimodal multi-objective optimization problems(MMOPs). In DRAS, relative contribution and improvement are utilized to define the aptitude of subspaces, which can capture the potentials of subspaces accurately. Moreover, the reinforcement learning method is used to dynamically allocate computing resources for each subspace. In addition, the proposed DRAS is applied to zoning searches. Experimental results demonstrate that DRAS can effectively assist zoning search in finding more and better distributed equivalent Pareto optimal solutions in the decision space.
