As an unsupervised learning method,stochastic competitive learning is commonly used for community detection in social network analysis.Compared with the traditional community detection algorithms,it has the advantage ...As an unsupervised learning method,stochastic competitive learning is commonly used for community detection in social network analysis.Compared with the traditional community detection algorithms,it has the advantage of realizing the time-series community detection by simulating the community formation process.In order to improve the accuracy and solve the problem that several parameters in stochastic competitive learning need to be pre-set,the author improves the algorithms and realizes improved stochastic competitive learning by particle position initialization,parameter optimization and particle domination ability self-adaptive.The experiment result shows that each improved method improves the accuracy of the algorithm,and the F1 score of the improved algorithm is 9.07%higher than that of original algorithm.展开更多
This paper is concerned with a three-species competitive model with both white noises and Levy noises. We first carry out the almost complete parameters analysis for the model and establish the critical value between ...This paper is concerned with a three-species competitive model with both white noises and Levy noises. We first carry out the almost complete parameters analysis for the model and establish the critical value between persistence in the mean and extinction for each species. The sufficient criteria for stability in distribution of solutions are obtained. Finally, numerical simulations are carried out to verify the theoretical results.展开更多
This paper discusses the dynamics of a Gilpin-Ayala competition model of two interacting species perturbed by white noise.We obtain the existence of a unique global positive solution of the system and the soluti...This paper discusses the dynamics of a Gilpin-Ayala competition model of two interacting species perturbed by white noise.We obtain the existence of a unique global positive solution of the system and the solution is bounded in pth moment.Then,we establish sufficient and necessary conditions for persistence and the existence of an ergodic stationary distribution of the model.We also establish sufficient conditions for extinction of the model.Moreover,numerical simulations are carried out for further support of present research.展开更多
基金This research was funded by National Natural Science Foundation of China(Grant No.2017YFC0820100)。
文摘As an unsupervised learning method,stochastic competitive learning is commonly used for community detection in social network analysis.Compared with the traditional community detection algorithms,it has the advantage of realizing the time-series community detection by simulating the community formation process.In order to improve the accuracy and solve the problem that several parameters in stochastic competitive learning need to be pre-set,the author improves the algorithms and realizes improved stochastic competitive learning by particle position initialization,parameter optimization and particle domination ability self-adaptive.The experiment result shows that each improved method improves the accuracy of the algorithm,and the F1 score of the improved algorithm is 9.07%higher than that of original algorithm.
基金The work is supported by National Science Foundation of China （No. 11472298）, the Fundamental Research Funds for the Central Universities （No. ZXH2012K004）, the National Science Foundation of Tianjin City （No. 13JCQNJC04400） and the NNSF of P. R. China （No. 11401574）.
文摘This paper is concerned with a three-species competitive model with both white noises and Levy noises. We first carry out the almost complete parameters analysis for the model and establish the critical value between persistence in the mean and extinction for each species. The sufficient criteria for stability in distribution of solutions are obtained. Finally, numerical simulations are carried out to verify the theoretical results.
基金supported by the National Natural Science Foundation of China(Nos.11871473 and 11801041)Foundation of Jilin Province Science and Technology Development(No.20190201130JC)+2 种基金Scientific Research Foundation of Jilin Provincial Education Department(Nos.JJKH20190503KJ and JJKH20181172KJ)the Natural Science Foundation of Changchun Normal University(No.2017-001)Shandong Provincial Natural Science Foundation(No.ZR2019MA010)。
文摘This paper discusses the dynamics of a Gilpin-Ayala competition model of two interacting species perturbed by white noise.We obtain the existence of a unique global positive solution of the system and the solution is bounded in pth moment.Then,we establish sufficient and necessary conditions for persistence and the existence of an ergodic stationary distribution of the model.We also establish sufficient conditions for extinction of the model.Moreover,numerical simulations are carried out for further support of present research.
