INTRODUCTIONLiver fibrosis is a dynamic course leading tocirrhosis from a various chronic liver diseases. Thepathological basis of fibrosis is the disturbance ofproduction and degradation of the extracellularmatrix (E...INTRODUCTIONLiver fibrosis is a dynamic course leading tocirrhosis from a various chronic liver diseases. Thepathological basis of fibrosis is the disturbance ofproduction and degradation of the extracellularmatrix (ECM), which causes accumulation of ECMin the liver[1,2].展开更多
A novel multi-dimensional scenario forecast approach which can capture the dynamic temporal-spatial interdependence relation among the outputs of multiple wind farms is proposed.In the proposed approach,support vector...A novel multi-dimensional scenario forecast approach which can capture the dynamic temporal-spatial interdependence relation among the outputs of multiple wind farms is proposed.In the proposed approach,support vector machine(SVM)is applied for the spot forecast of wind power generation.The probability density function(PDF)of the SVM forecast error is predicted by sparse Bayesian learning(SBL),and the spot forecast result is corrected according to the error expectation obtained.The copula function is estimated using a Gaussian copula-based dynamic conditional correlation matrix regression(DCCMR)model to describe the correlation among the errors.And the multidimensional scenario is generated with respect to the estimated marginal distributions and the copula function.Test results on three adjacent wind farms illustrate the effectiveness of the proposed approach.展开更多
频繁项集挖掘算法的计算复杂性和生成的频繁项集数量随着事务集项数的增加呈指数增长,最小支持度阈值成为控制这种增长的关键.然而,实际应用中仅使用支持度阈值难以有效控制频繁项集的规模.为此定义 N 个最频繁项集挖掘问题,并提出基于...频繁项集挖掘算法的计算复杂性和生成的频繁项集数量随着事务集项数的增加呈指数增长,最小支持度阈值成为控制这种增长的关键.然而,实际应用中仅使用支持度阈值难以有效控制频繁项集的规模.为此定义 N 个最频繁项集挖掘问题,并提出基于支持度阈值动态调整策略的宽度优先搜索算法 NApriori 和深度优先搜索算法IntvMatrix 挖掘 N 个最频繁项集.实验表明,本文的2种方法的效率比朴素方法高2倍以上,特别当 N 值较低时,本文方法的效率优势更为明显.展开更多
基金Project supported by the National Natural Science Foundation of China, No. 39500138
文摘INTRODUCTIONLiver fibrosis is a dynamic course leading tocirrhosis from a various chronic liver diseases. Thepathological basis of fibrosis is the disturbance ofproduction and degradation of the extracellularmatrix (ECM), which causes accumulation of ECMin the liver[1,2].
基金This work is supported by National Natural Science Foundation of China(No.51007047,No.51077087)Shandong Provincial Natural Science Foundation of China(No.20100131120039)National High Technology Research and Development Program of China(863 Program)(No.2011AA05A101).
文摘A novel multi-dimensional scenario forecast approach which can capture the dynamic temporal-spatial interdependence relation among the outputs of multiple wind farms is proposed.In the proposed approach,support vector machine(SVM)is applied for the spot forecast of wind power generation.The probability density function(PDF)of the SVM forecast error is predicted by sparse Bayesian learning(SBL),and the spot forecast result is corrected according to the error expectation obtained.The copula function is estimated using a Gaussian copula-based dynamic conditional correlation matrix regression(DCCMR)model to describe the correlation among the errors.And the multidimensional scenario is generated with respect to the estimated marginal distributions and the copula function.Test results on three adjacent wind farms illustrate the effectiveness of the proposed approach.
文摘频繁项集挖掘算法的计算复杂性和生成的频繁项集数量随着事务集项数的增加呈指数增长,最小支持度阈值成为控制这种增长的关键.然而,实际应用中仅使用支持度阈值难以有效控制频繁项集的规模.为此定义 N 个最频繁项集挖掘问题,并提出基于支持度阈值动态调整策略的宽度优先搜索算法 NApriori 和深度优先搜索算法IntvMatrix 挖掘 N 个最频繁项集.实验表明,本文的2种方法的效率比朴素方法高2倍以上,特别当 N 值较低时,本文方法的效率优势更为明显.
