在对当前分布式数据库技术,特别是分布式数据库管理系统进行分析的基础上,运用开源Amoeba for A ladd in项目对如何搭建分布式的网络教学资源平台进行全面阐述,探讨网络教学资源平台的整体和局部设计,进而提出一种在网络教学资源平台中...在对当前分布式数据库技术,特别是分布式数据库管理系统进行分析的基础上,运用开源Amoeba for A ladd in项目对如何搭建分布式的网络教学资源平台进行全面阐述,探讨网络教学资源平台的整体和局部设计,进而提出一种在网络教学资源平台中实现分布式数据库的方法.最终设计并实现一套通用的分布式网络教学资源平台.结合分布式数据库技术来设计网络教学系统可实现教学资源更大范围的共享与整合.展开更多
The solutions of dynamic optimization problems are usually very difficult due to their highly nonlinear and multidimensional nature. 13enetic algorithm （GA） has been proved to be a teasibte method when the gradient ...The solutions of dynamic optimization problems are usually very difficult due to their highly nonlinear and multidimensional nature. 13enetic algorithm （GA） has been proved to be a teasibte method when the gradient is difficult to calculate. Its advantage is that the control profiles at all time stages are optimized simultaneously, but its convergence is very slow in the later period of evolution and it is easily trapped in the local optimum. In this study, a hybrid improved genetic algorithm （HIGA） for solving dynamic optimization problems is proposed to overcome these defects. Simplex method （SM） is used to perform the local search in the neighborhood of the optimal solution. By using SM, the ideal searching direction of global optimal solution could be found as soon as possible and the convergence speed of the algorithm is improved. The hybrid algorithm presents some improvements, such as protecting the best individual, accepting immigrations, as well as employing adaptive crossover and Ganssian mutation operators. The efficiency of the proposed algorithm is demonstrated by solving several dynamic optimization problems. At last, HIGA is applied to the optimal production of secreted protein in a fed batch reactor and the optimal feed-rate found by HIGA is effective and relatively stable.展开更多
By adopting the chaotic searching to improve the global searching performance of the particle swarm optimization (PSO), and using the improved PSO to optimize the key parameters of the support vector machine (SVM) for...By adopting the chaotic searching to improve the global searching performance of the particle swarm optimization (PSO), and using the improved PSO to optimize the key parameters of the support vector machine (SVM) forecasting model, an improved SVM model named CPSO-SVM model was proposed. The new model was applied to predicting the short term load, and the improved effect of the new model was proved. The simulation results of the South China Power Market’s actual data show that the new method can effectively improve the forecast accuracy by 2.23% and 3.87%, respectively, compared with the PSO-SVM and SVM methods. Compared with that of the PSO-SVM and SVM methods, the time cost of the new model is only increased by 3.15 and 4.61 s, respectively, which indicates that the CPSO-SVM model gains significant improved effects.展开更多
A new multi-species particle swarm optimization with a two-level hierarchical topology and the orthogonal learning strategy(OMSPSO) is proposed, which enhances the global search ability of particles and increases thei...A new multi-species particle swarm optimization with a two-level hierarchical topology and the orthogonal learning strategy(OMSPSO) is proposed, which enhances the global search ability of particles and increases their convergence rates. The numerical results on 10 benchmark functions demonstrated the effectiveness of our proposed algorithm. Then, the proposed algorithm is presented to design a butterfly-shaped microstrip patch antenna. Combined with the HFSS solver, a butterfly-shaped patch antenna with a bandwidth of about 40.1% is designed by using the proposed OMSPSO. The return loss of the butterfly-shaped antenna is greater than 10 d B between 4.15 and 6.36 GHz. The antenna can serve simultaneously for the high-speed wireless computer networks(5.15–5.35 GHz) and the RFID systems(5.8 GHz).展开更多
In order to evaluate the level of the coal mine essential safety management, the comprehensive index system was designed base on the connotation principle of the mine essential safety management. Due to the disadvanta...In order to evaluate the level of the coal mine essential safety management, the comprehensive index system was designed base on the connotation principle of the mine essential safety management. Due to the disadvantage of index weight setting by subjective idea in the former method, support vector classification algorithm was used to assess the level of coal mine essential safety management. According to the advantages of the global search capability of the genetic algorithm, support vector classification parameters optimization method was proposed based on genetic algorithm, and genetic algorithm-support vector classification model of coal mine essential safety management assessment was established. Learning samples were constructed on the basis of former data of mine essential safety management evaluation. The test results show that the genetic algorithm-support vector classification model has higher evaluation accuracy and good generalization ability, and the advantage of no need for artificial setting of index weight and absence of the subjective factors influence to evaluation results.展开更多
In this paper,a class of new geometric flows on a complete Riemannian manifold is defined. The new flow is related to the generalized（third order） Landau-Lifshitz equation. On the other hand it could be thought of a...In this paper,a class of new geometric flows on a complete Riemannian manifold is defined. The new flow is related to the generalized（third order） Landau-Lifshitz equation. On the other hand it could be thought of as a special case of the Schroodinger-Airy flow when the target manifold is a Koahler manifold with constant holomorphic sectional curvature. We show the local existence of the new flow on a complete Riemannian manifold with some assumptions on Ricci tensor. Moreover,if the target manifolds are Einstein or some certain type of locally symmetric spaces,the global results are obtained.展开更多
文摘在对当前分布式数据库技术,特别是分布式数据库管理系统进行分析的基础上,运用开源Amoeba for A ladd in项目对如何搭建分布式的网络教学资源平台进行全面阐述,探讨网络教学资源平台的整体和局部设计,进而提出一种在网络教学资源平台中实现分布式数据库的方法.最终设计并实现一套通用的分布式网络教学资源平台.结合分布式数据库技术来设计网络教学系统可实现教学资源更大范围的共享与整合.
基金Supported by Major State Basic Research Development Program of China （2012CB720500）, National Natural Science Foundation of China （Key Program： Ul162202）, National Science Fund for Outstanding Young Scholars （61222303）, National Natural Science Foundation of China （21276078, 21206037） and the Fundamental Research Funds for the Central Universities.
文摘The solutions of dynamic optimization problems are usually very difficult due to their highly nonlinear and multidimensional nature. 13enetic algorithm （GA） has been proved to be a teasibte method when the gradient is difficult to calculate. Its advantage is that the control profiles at all time stages are optimized simultaneously, but its convergence is very slow in the later period of evolution and it is easily trapped in the local optimum. In this study, a hybrid improved genetic algorithm （HIGA） for solving dynamic optimization problems is proposed to overcome these defects. Simplex method （SM） is used to perform the local search in the neighborhood of the optimal solution. By using SM, the ideal searching direction of global optimal solution could be found as soon as possible and the convergence speed of the algorithm is improved. The hybrid algorithm presents some improvements, such as protecting the best individual, accepting immigrations, as well as employing adaptive crossover and Ganssian mutation operators. The efficiency of the proposed algorithm is demonstrated by solving several dynamic optimization problems. At last, HIGA is applied to the optimal production of secreted protein in a fed batch reactor and the optimal feed-rate found by HIGA is effective and relatively stable.
基金Project(70572090) supported by the National Natural Science Foundation of China
文摘By adopting the chaotic searching to improve the global searching performance of the particle swarm optimization (PSO), and using the improved PSO to optimize the key parameters of the support vector machine (SVM) forecasting model, an improved SVM model named CPSO-SVM model was proposed. The new model was applied to predicting the short term load, and the improved effect of the new model was proved. The simulation results of the South China Power Market’s actual data show that the new method can effectively improve the forecast accuracy by 2.23% and 3.87%, respectively, compared with the PSO-SVM and SVM methods. Compared with that of the PSO-SVM and SVM methods, the time cost of the new model is only increased by 3.15 and 4.61 s, respectively, which indicates that the CPSO-SVM model gains significant improved effects.
基金Project(61105067)supported by the National Natural Science Foundation of China
文摘A new multi-species particle swarm optimization with a two-level hierarchical topology and the orthogonal learning strategy(OMSPSO) is proposed, which enhances the global search ability of particles and increases their convergence rates. The numerical results on 10 benchmark functions demonstrated the effectiveness of our proposed algorithm. Then, the proposed algorithm is presented to design a butterfly-shaped microstrip patch antenna. Combined with the HFSS solver, a butterfly-shaped patch antenna with a bandwidth of about 40.1% is designed by using the proposed OMSPSO. The return loss of the butterfly-shaped antenna is greater than 10 d B between 4.15 and 6.36 GHz. The antenna can serve simultaneously for the high-speed wireless computer networks(5.15–5.35 GHz) and the RFID systems(5.8 GHz).
基金Supported by the National Nature Science Foundation of China （51174082） the Doctoral Research Fund of Henan Polytechnic University （B2010-69 B2011-056） the Guidance Program for Science and Technology Research of China National Coal Association （MTKJ2010-383）
文摘In order to evaluate the level of the coal mine essential safety management, the comprehensive index system was designed base on the connotation principle of the mine essential safety management. Due to the disadvantage of index weight setting by subjective idea in the former method, support vector classification algorithm was used to assess the level of coal mine essential safety management. According to the advantages of the global search capability of the genetic algorithm, support vector classification parameters optimization method was proposed based on genetic algorithm, and genetic algorithm-support vector classification model of coal mine essential safety management assessment was established. Learning samples were constructed on the basis of former data of mine essential safety management evaluation. The test results show that the genetic algorithm-support vector classification model has higher evaluation accuracy and good generalization ability, and the advantage of no need for artificial setting of index weight and absence of the subjective factors influence to evaluation results.
基金supported by National Natural Science Foundation of China(Grant Nos.11226082,11301557 and 10990013)
文摘In this paper,a class of new geometric flows on a complete Riemannian manifold is defined. The new flow is related to the generalized（third order） Landau-Lifshitz equation. On the other hand it could be thought of as a special case of the Schroodinger-Airy flow when the target manifold is a Koahler manifold with constant holomorphic sectional curvature. We show the local existence of the new flow on a complete Riemannian manifold with some assumptions on Ricci tensor. Moreover,if the target manifolds are Einstein or some certain type of locally symmetric spaces,the global results are obtained.
