http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
A Model for Coopetition Evolution of Software Industrial Virtual Cluster
Liu Kewen,Gao Changyuan 보안공학연구지원센터 2016 International Journal of Grid and Distributed Comp Vol.9 No.3
The application of complex network theory can clearly reveal the coopetition activities between inter-members in software industrial virtual cluster. The research result shows that neither simplex cooperation nor competition,but it is a kind of dynamic equilibrium of coopetition. The empirical is analyzed by using the example of cloud computing. In the process of coopetition evolution, the distribution functions of node strength are from random to power law and eventually to random.
Coopetition Co-existence Model for Software Industrial Virtual Cluster Based on Business Ecosystems
Liu Kewen,Gao Changyuan 보안공학연구지원센터 2016 International Journal of u- and e- Service, Scienc Vol.9 No.6
Coopetition is an important driving force for the formation and sustainable development of Software Industrial Virtual Clusters. But the process of participating in the global coopetition of software enterprises is very complicated. This paper analyzed the characteristic of coopetition in Software Industrial Virtual Clusters by using the theory of business ecosystems, coopetition co-existence model of Software Industrial Virtual Cluster was established, introducing competition coefficient and cooperation coefficient on the basis of Tilman’s research. The results of simulation show that the condition of coopetition co-existence is the competitive ability has a nonlinear minus correlation with cooperation ability. The empirical study also found that the initial share is an important factor affecting the competitive advantage.
The Framework of Social Networks Big Data Processing Based on Cloud Computing
Liu Kewen,Gao Changyuan 보안공학연구지원센터 2016 International Journal of Database Theory and Appli Vol.9 No.10
With the rise of cloud computing, internet of things, social networks, the type and scale of data in human society has increased at an unprecedented rate, making data from being a simple object to be process to being a basic resource. Fully mining the value of data resources that was hidden in SNS such Weibo Microblog, Wechat has become a common subject concerned by industrial circle, academic area and government departments. Although the distributed storage and analysis of cloud computing platform have been widely used in big data process of social networks, it has not been able to fully solve the problems of big data storage and process in social networks. In this paper, it proposed the big data process framework of social networks based on cloud computing. By adopting the mixing cloud model and coordinating the data storage framework and data computing framework, and regarding social networks features such as real-time, sharing, mobility, individuation, and interactivity, this big data process framework can be adopted to process large-scale massive amount of data, to research the unified management and sharing strategy of massive data, to propose data process strategy and the service application of big data such as Microblog and Wechat, and to discuss several urgent key problems in processing social networks big data.
Robust Fractional Embedded Cubature Kalman Filter for Fractional Nonlinear Stochastic System
Jing Mu,Changyuan Wang,Wuqi Gao,Feng Tian,Jianlian Cheng 제어·로봇·시스템학회 2022 International Journal of Control, Automation, and Vol.20 No.11
In this study, the fractional embedded cubature Kalman filter (FECKF) and robust fractional embedded cubature Kalman filter (RoFECKF) are proposed to design the estimate the states for fractional-order nonlinear discrete systems with Gaussian and non-Gaussian measurement noise, respectively. We develop FECKF algorith by extending embedded cubature Kalman filter to fractional nonlinear stochastic system with Gaussian noise. Meanwhile, RoFECKF is put forward to increase the estimation robustness under noisy measurements by applying the Huber method to FECKF. Simulation results on adaptive system identification and re-entry target tracking system demonstrate the effectiveness and robustness of the proposed approach.