A detailed study of some simple forms which have a given special structure have been solved, in this paper, we research the extension of this kind of special structure problems.
Intensity of competition, especially global competition, has driven many organizations to search for innovative ways to improve productivity and performance. This trend has led many firms to adopt approaches to implem...Intensity of competition, especially global competition, has driven many organizations to search for innovative ways to improve productivity and performance. This trend has led many firms to adopt approaches to implement cloud systems. Cloud systems have distinct characteristics that differentiate it from traditional internet services, due to a number of significant innovation factors. For example, firms need improved access to high-speed intemet as well as access to customer relationship management （CRM） and enterprise resource planning （ERP） capacities. This means that the interest of many firms in the implementation of cloud systems has increased. Although cloud systems are designed to facilitate knowledge transfer, currently, there is no method to ensure that knowledge transfer is useful or relevant to a firm. This in turn means that finns need to ensure that the cloud system has the capabilities to screen knowledge for compliance against some known knowledge characteristics. The use of cloud systems could result in an efficient delivery of innovation knowledge in an effective way. This paper presents an approach for assessment of the successful implementation of cloud systems. This paper also discusses the various success factors of cloud systems for global innovation.展开更多
Generation of wind power time series is an important foundational task for assisting electric power system planning and mak- ing decision. By analyzing the characteristics of wind power persistence and variation, th!....Generation of wind power time series is an important foundational task for assisting electric power system planning and mak- ing decision. By analyzing the characteristics of wind power persistence and variation, th!.s paper proposes an improved Mar- kov chain Monte Carlo （MCMC） method, identified as the PV-MC method, for the direct generation of a synthetic series of wind power output. On the basis of the MCMC method, duration time and variation features are concluded in PV-MC method, gaining a more comprehensive reflection of wind power characteristics in the generated wind power time series. First, the wind power state series is generated to meet the state transition matrix based on the definition of the wind power state. Then, the time duration of each state in the series is determined by its respective duration character. Finally, the variation characteristic is used to convert the state series to a wind power time series. A significant amount of simulations are performed based on the PV-MC and MCMC methods and are then compared for 25 wind farms at 6 different locations throughout the world. The sim- ulation results show that the PV-MC method offers an excellent fit for the time domain features （persistence and variation characteristic） while holding other statistic features （mean value, variance, autocorrelation coefficient （ACC） and probability density function （PDF）） close to the MCMC method.展开更多
文摘A detailed study of some simple forms which have a given special structure have been solved, in this paper, we research the extension of this kind of special structure problems.
文摘Intensity of competition, especially global competition, has driven many organizations to search for innovative ways to improve productivity and performance. This trend has led many firms to adopt approaches to implement cloud systems. Cloud systems have distinct characteristics that differentiate it from traditional internet services, due to a number of significant innovation factors. For example, firms need improved access to high-speed intemet as well as access to customer relationship management （CRM） and enterprise resource planning （ERP） capacities. This means that the interest of many firms in the implementation of cloud systems has increased. Although cloud systems are designed to facilitate knowledge transfer, currently, there is no method to ensure that knowledge transfer is useful or relevant to a firm. This in turn means that finns need to ensure that the cloud system has the capabilities to screen knowledge for compliance against some known knowledge characteristics. The use of cloud systems could result in an efficient delivery of innovation knowledge in an effective way. This paper presents an approach for assessment of the successful implementation of cloud systems. This paper also discusses the various success factors of cloud systems for global innovation.
基金supported by the National Natural Science Foundation of China(Grant No.51377027)the National Basic Research Program of China("973"Project)(Grant No.2012CB215104)ABB(China)Ltd
文摘Generation of wind power time series is an important foundational task for assisting electric power system planning and mak- ing decision. By analyzing the characteristics of wind power persistence and variation, th!.s paper proposes an improved Mar- kov chain Monte Carlo （MCMC） method, identified as the PV-MC method, for the direct generation of a synthetic series of wind power output. On the basis of the MCMC method, duration time and variation features are concluded in PV-MC method, gaining a more comprehensive reflection of wind power characteristics in the generated wind power time series. First, the wind power state series is generated to meet the state transition matrix based on the definition of the wind power state. Then, the time duration of each state in the series is determined by its respective duration character. Finally, the variation characteristic is used to convert the state series to a wind power time series. A significant amount of simulations are performed based on the PV-MC and MCMC methods and are then compared for 25 wind farms at 6 different locations throughout the world. The sim- ulation results show that the PV-MC method offers an excellent fit for the time domain features （persistence and variation characteristic） while holding other statistic features （mean value, variance, autocorrelation coefficient （ACC） and probability density function （PDF）） close to the MCMC method.
