1) time-varying weight
非负时变权
1.
Our purpose in this paper is to development a new algorithm formula to fit combinatorial forecasting with nonnegative time-varying weight by use of Markov chain.
通过马氏链拟合的方法求取一种新的非负时变权组合预测算法公式。
2) nonnegative timevariant weights
非负可变权重
1.
Based on paper and ,the combination forecasting model of nonnegative timevariant weights is put forward.
本文在文献［１］和［２］的基础上，建立了非负可变权重的组合预测模型，并利用线性规划和二次规划模型，给出了在拟合点上最优的非负可变权重的计算方法，最后也探讨了在预测点上非负可变权重的估计。
4) nonnegative weights
权值非负
1.
A new kind algorithm of Kriging based on the Linear Programming (LP)is proposed to take the constrains of nonnegative weights into consideration,and this new method not only makes the use of LP's properties of easy and fast caculation,but also avoids the heavy caculation and subjective affection that existed in the other methods with nonnegative weights.
基于线性规划方法提出了一种考虑权值非负约束的克立格算法，该算法既利用了线性规划求解简便、快捷的优点，又克服了其它正克立格法计算工作量大以及受主观因素影响的缺点。
5) non-negative weights
非负权重
1.
Combined the characteristics of three forecast methods,a forecast model with non-negative weights is proposed.
本文根据1998年~2005年江苏省入境旅游客源数据特征,采用BP神经网络模型、GM(1,1)模型以及指数曲线模型分别进行预测,然后结合这三种预测方法的特点,提出非负权重组合预测模型,通过实例运算的对比分析,证明组合预测模型具有很高的准确性。
6) non-negative weight
非负权重
1.
An Iterative Algorithm for Optimal Combination Forcasting of Non-negative Weights;
非负权重最优组合预测的迭代算法研究
2.
The paper is based on the limit theory and former person s research on arithmetic for optimal combination forecasting of non-negative weights.
在极限理论及其前人对非负权重最优组合算法研究的基础之上,提出了一种求解非负权重近似最优解的简明算法,并进行了实例分析,结果令人满意,验证了该方法的实用性和有效性。
3.
On the basis of rational choice of single forecast model,through the solution of approximate optimal non-negative weight,creates an combination forecasting model.
在合理选择单一预测模型的基础上,通过求解近似最优非负权重来建立组合预测模型,并运用概率统计方法对模型的适用性进行了验证,为浙江省公路货运量的预测提供了新思路。
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参考词条