Presently T-wave alternans (TWA) has become a clinical index of non-invasive diagnosis for heart sudden death prediction, and detecting T-wave alternate accurately is particularly important. This paper introduces an a...Presently T-wave alternans (TWA) has become a clinical index of non-invasive diagnosis for heart sudden death prediction, and detecting T-wave alternate accurately is particularly important. This paper introduces an algorithm for detecting TWA using Poincare mapping method which is a technique for nonlinear dynamic systems to display periodic behavior. Sample series of beat to beat cycles were selected to prepare Poincare mapping method. Vector Angle Index (VAI), which is the mean of the difference between θi (the angle between the line connecting the i point to the origin and the X axis) and 45 degrees was used to present the presence or absence of TWA. The value of 0.9 rad ≤ VAI ≤ 1.03 rad is accepted as a level determinative for presence of TWA. VAI via Poincare mapping method (PM) is used for correlation analysis with T-wave alternans voltage (Vtwa) by way of the spectral method (SM). The cross-correlation coefficient between Vtwa and VAI is γ = 0.8601. The algorithm can identify the absence and presence of TWA accurately and provide idea for further study of TWA-PM.展开更多
随着电网公司代理购电业务稳步推进,代理购电业务体系逐步完善,精确的代理购电用户用电量预测为保障电力安全稳定供应奠定了基础。因此,文章构建自适应权重组合模型,将不同校核方法的校核结果进行权重分配,从而提升校核结果准确性。首先...随着电网公司代理购电业务稳步推进,代理购电业务体系逐步完善,精确的代理购电用户用电量预测为保障电力安全稳定供应奠定了基础。因此,文章构建自适应权重组合模型,将不同校核方法的校核结果进行权重分配,从而提升校核结果准确性。首先,构建预测业务偏差校核流程框架,确定代理购电预测业务校核流程。然后分别选取分位数映射法、增量变化法以及支持向量回归(support vector regression,SVR)对预测结果进行校核,得到同一纬度下的不同方法校核结果。最后,建立遗传算法-优劣解距离法(genetic algorithm-technique for order preference by similarity to ideal solution,GA-TOPSIS)模型针对校核结果进行准确性与稳定性双目标优化,选取不同校核方法的最优权重组合。测试结果表明在校核方法权重组合校正后,相较于初始预测值和单一校核方法校核后的结果,预测精度和准确度得到明显提升。展开更多
文摘Presently T-wave alternans (TWA) has become a clinical index of non-invasive diagnosis for heart sudden death prediction, and detecting T-wave alternate accurately is particularly important. This paper introduces an algorithm for detecting TWA using Poincare mapping method which is a technique for nonlinear dynamic systems to display periodic behavior. Sample series of beat to beat cycles were selected to prepare Poincare mapping method. Vector Angle Index (VAI), which is the mean of the difference between θi (the angle between the line connecting the i point to the origin and the X axis) and 45 degrees was used to present the presence or absence of TWA. The value of 0.9 rad ≤ VAI ≤ 1.03 rad is accepted as a level determinative for presence of TWA. VAI via Poincare mapping method (PM) is used for correlation analysis with T-wave alternans voltage (Vtwa) by way of the spectral method (SM). The cross-correlation coefficient between Vtwa and VAI is γ = 0.8601. The algorithm can identify the absence and presence of TWA accurately and provide idea for further study of TWA-PM.
文摘随着电网公司代理购电业务稳步推进,代理购电业务体系逐步完善,精确的代理购电用户用电量预测为保障电力安全稳定供应奠定了基础。因此,文章构建自适应权重组合模型,将不同校核方法的校核结果进行权重分配,从而提升校核结果准确性。首先,构建预测业务偏差校核流程框架,确定代理购电预测业务校核流程。然后分别选取分位数映射法、增量变化法以及支持向量回归(support vector regression,SVR)对预测结果进行校核,得到同一纬度下的不同方法校核结果。最后,建立遗传算法-优劣解距离法(genetic algorithm-technique for order preference by similarity to ideal solution,GA-TOPSIS)模型针对校核结果进行准确性与稳定性双目标优化,选取不同校核方法的最优权重组合。测试结果表明在校核方法权重组合校正后,相较于初始预测值和单一校核方法校核后的结果,预测精度和准确度得到明显提升。
