Numerical tests of efficiency of the retrospective time integration scheme in the self-memory model

A set of numerical tests was carried out to compare the retrospective time integral scheme in a self-memory model,whose dynamic kernel is the barotropical quasi-geostrophic model, with the ordinary centered difference scheme in the barotropical quasigeostrophic model. The Rossby-Haurwitz wave function was taken as the initial fields for both schemes. The results show that in comparison with the ordinary centered difference scheme, the retrospective time integral scheme reduces by 2 orders of magnitude the forecast error, and the forecast error increases very little with lengthening of the time-step. Therefore, the retrospective time integral scheme has advantages of improving the forecast accuracy, extending the predictable duration and reducing the computation amount.     

灰色自记忆模型及应用

导出了GM（1，1）模型微分方程的自记忆计算格式，建立了一种新的对历史多个时刻观测数据具有记忆功能的灰色自记忆模型，模型克服了GM（1，1）模型“对初值比较敏感”，预见期短和序列数据非负的局限，并有效提高了模型的计算精度。大量数值计算结果充分表明了该模型具有精度高，稳定性好的优点。     

水电站入库流量的灰色自记忆预测方法研究

运用灰色系统理论与数据序列自记忆性原理相结合的方法,提出了数据序列预测的灰色自记忆模型,并应用于年径流量及汛期来水预测.山西沁河曹河水电站年径流及汛期径流预测的实例表明,该模型能处理非平稳数据序列并反映动态数据序列的极值趋势,可提高预测精度.     

融合自忆性原理的优化GM(1,1)幂模型构建及应用

针对因发展变化受众多因素影响而具有饱和增长趋势或单峰特性的原始波动序列,为了提高预测精度,以灰色GM(1,1)幂模型为基础,构建了自忆性原理与优化GM(1,1)幂模型的耦合预测模型,用动力系统自忆性原理来克服传统灰色模型对初值比较敏感的弱点。结果表明,新构建模型能够充分利用系统的多个历史时次资料,模拟和预测精度都高于传统优化GM(1,1)幂模型,进一步拓展了灰色模型的应用范围。最后,以我国高中升学率的数据为例验证了所构建模型的优越性和有效性。     

umerical tests of efficiency of the retrospective time integration scheme in the self-memory model

Althoughthedesignofcomputingschemeinthenumericalweatherpredictionismainlytoimprovethespacialdifference,theresearchforimprovingthetimedifferenceschemehasseenapparentprogresses[1～5].Itisconfirmedthattheretrospectivetimeintegralschemeadoptedinaspectrummodel,whichutilizesmultitimehistoricaldata,improvestheaccuracyofthenumericalweatherprediction[6,7].Inthisarticle,weapplytheretrospectivetimeintegralschemetoasimpledifferencemodel,performnumericalexperimentsandpresentacomparisonanalysis.1　Principle…     

Logistic自记忆模型在国民经济预测中的应用

运用改进单纯型法、Logistic自记忆模型对国民经济进行预测,并与钟建生等的预测结果进行比较.结果表明:改进单纯型法优于线性变换法;Logistic自记忆模型优于Logistic模型.该研究为各行各业的预测提供了一种新的思路和方法.