随着数据量的爆炸式增长,边缘计算在大数据处理中的作用愈加重要.现实应用中产生的数据通常建模表示成高阶增量式张量的形式,增量式张量Tucker分解是一种高效挖掘高阶海量数据中隐藏信息的方法.针对传统增量式张量分解忽视张量模特征对...随着数据量的爆炸式增长,边缘计算在大数据处理中的作用愈加重要.现实应用中产生的数据通常建模表示成高阶增量式张量的形式,增量式张量Tucker分解是一种高效挖掘高阶海量数据中隐藏信息的方法.针对传统增量式张量分解忽视张量模特征对分解过程的影响、分解结果不能较好保留原始数据特征的问题,提出一种基于模特征的增量式张量Tucker分解方法 ITTDMC (incremental tensor tucker decomposition based on mode characteristics).首先,用模长增量决定增量因子矩阵更新顺序,以此降低更新顺序带来的重构误差;其次,根据模熵变化比决定增量因子矩阵更新权重,使分解结果更准确保留各模特征;然后,将过往时刻的模特征和更新参数记录在指导张量中,遇到模特征相似的增量数据时直接使用来指导张量中参数的更新,避免重复计算,降低时间开销;最后,在合成和真实数据集上进行大量的实验,实验结果表明ITTDMC在模特征明显的数据集上能显著降低(最高可达29%)增量式张量的重构误差.展开更多
As a key factor of economic growth, productivity has been valued in the academic community. Today, with the rapid development of service industry, the research for service productivity has also attracted wide attentio...As a key factor of economic growth, productivity has been valued in the academic community. Today, with the rapid development of service industry, the research for service productivity has also attracted wide attention. However, in the service industry, because of its own characteristics and properties, measurement of service productivity could not apply for the traditional productivity measurement methods simply. This research first has put out the constitution model of service productivity, and thus put out the measurement model of service productivity. And explains that service productivity is a function which contains internal efficiency, external efficiency, and capacity efficiency. In service productivity, external efficiency is the key one, internal efficie and capacity efficiency should also be given considerations. Eventually, the strategy of implementing measurement of service productivity have been proposed ncy the展开更多
In this paper,the authors have made the following findings after the fitting of China's economic growth rate series using an improved STR model:since 1949,great changes have taken place in China's economic gro...In this paper,the authors have made the following findings after the fitting of China's economic growth rate series using an improved STR model:since 1949,great changes have taken place in China's economic growth pattern but factor input remains to be the major source of China's economic growth,as reflected by the extensive pattern of economic growth;with the exception of capital,the marginal output of all other production factors has been on the increase,which suggests that the efficiency of China's factor allocation has been continuously improved;the marginal output of capital has been on the decline,which explains that the dependency on investment for economic growth has led to excessive investment;reform and opening up and reform of marketization have substantially increased the sustainability of China's economic growth.In addition,the authors have investigated the internal momentum of China's growth transformation and developed relevant policy recommendations.展开更多
Taking full account of the synergistic effects of multidimensional factors on regional economic growth in China, this paper constructs a model of the spatial spillover effects of transport infrastructure on regional e...Taking full account of the synergistic effects of multidimensional factors on regional economic growth in China, this paper constructs a model of the spatial spillover effects of transport infrastructure on regional economic growth. Using provincial panel data from 1993 to 2009 and employing spatial econometric techniques, our empirical analysis comes to the following conclusions. (1) The total output elasticity of transport infrastructure for regional economic growth varies between 0.05 and 0.07, indicating its important role in such growth. (2) Transport infrastructure has very clear spatial spillover effects on regional economic growth; its role in regional economic growth will be overestimated if these are neglected. (3) For a specific region, transport infrastructure in other regions has mainly positive spillover effects on economic growth, but there is also evidence of negative spillover effects. (4) Among multidimensional factors contributing to regional economic growth, labor pluscapital stock from other parts of the public sector make the greatest contribution to regional economic growth in China, followed by the new economic growth factors and new economic geography.展开更多
文摘随着数据量的爆炸式增长,边缘计算在大数据处理中的作用愈加重要.现实应用中产生的数据通常建模表示成高阶增量式张量的形式,增量式张量Tucker分解是一种高效挖掘高阶海量数据中隐藏信息的方法.针对传统增量式张量分解忽视张量模特征对分解过程的影响、分解结果不能较好保留原始数据特征的问题,提出一种基于模特征的增量式张量Tucker分解方法 ITTDMC (incremental tensor tucker decomposition based on mode characteristics).首先,用模长增量决定增量因子矩阵更新顺序,以此降低更新顺序带来的重构误差;其次,根据模熵变化比决定增量因子矩阵更新权重,使分解结果更准确保留各模特征;然后,将过往时刻的模特征和更新参数记录在指导张量中,遇到模特征相似的增量数据时直接使用来指导张量中参数的更新,避免重复计算,降低时间开销;最后,在合成和真实数据集上进行大量的实验,实验结果表明ITTDMC在模特征明显的数据集上能显著降低(最高可达29%)增量式张量的重构误差.
文摘As a key factor of economic growth, productivity has been valued in the academic community. Today, with the rapid development of service industry, the research for service productivity has also attracted wide attention. However, in the service industry, because of its own characteristics and properties, measurement of service productivity could not apply for the traditional productivity measurement methods simply. This research first has put out the constitution model of service productivity, and thus put out the measurement model of service productivity. And explains that service productivity is a function which contains internal efficiency, external efficiency, and capacity efficiency. In service productivity, external efficiency is the key one, internal efficie and capacity efficiency should also be given considerations. Eventually, the strategy of implementing measurement of service productivity have been proposed ncy the
基金supported by the Evaluation of China's Structural Dividend and Research on Relevant Policiesa Special Program of Cultural and Social Sciences Key Research Center of the Department of Education,Liaoning Province(GrantNo.Z J2013046)
文摘In this paper,the authors have made the following findings after the fitting of China's economic growth rate series using an improved STR model:since 1949,great changes have taken place in China's economic growth pattern but factor input remains to be the major source of China's economic growth,as reflected by the extensive pattern of economic growth;with the exception of capital,the marginal output of all other production factors has been on the increase,which suggests that the efficiency of China's factor allocation has been continuously improved;the marginal output of capital has been on the decline,which explains that the dependency on investment for economic growth has led to excessive investment;reform and opening up and reform of marketization have substantially increased the sustainability of China's economic growth.In addition,the authors have investigated the internal momentum of China's growth transformation and developed relevant policy recommendations.
基金the Youth Project of the National Social Science Foundation "Studies on the Spatial Spillover Effects of Transport Infrastructure on Chinese Regional Economic Growth" (No.70803030)the Shanghai "Shuguang" Project of 2011(No.11SG36)the Key Scientific Research Innovation Project of the Shanghai Education Commission(No.10ZS50)
文摘Taking full account of the synergistic effects of multidimensional factors on regional economic growth in China, this paper constructs a model of the spatial spillover effects of transport infrastructure on regional economic growth. Using provincial panel data from 1993 to 2009 and employing spatial econometric techniques, our empirical analysis comes to the following conclusions. (1) The total output elasticity of transport infrastructure for regional economic growth varies between 0.05 and 0.07, indicating its important role in such growth. (2) Transport infrastructure has very clear spatial spillover effects on regional economic growth; its role in regional economic growth will be overestimated if these are neglected. (3) For a specific region, transport infrastructure in other regions has mainly positive spillover effects on economic growth, but there is also evidence of negative spillover effects. (4) Among multidimensional factors contributing to regional economic growth, labor pluscapital stock from other parts of the public sector make the greatest contribution to regional economic growth in China, followed by the new economic growth factors and new economic geography.