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时间序列分析VC源码
- 时间序列分析,分析序列是否是 白色噪声,分析相关性,可以进一步判断序列的相关和自相关-time series analysis, whether the sequence is white noise, correlation analysis, further sequence of judgment and autocorrelation
grey
- 灰色关联度程序,可以用于变量相关性分析并可以用于决策。
AlarmCorrelationModel
- 介绍告警相关性分析及其相关研究,并提出了1 个通用的告警相关性分析模型. 在分析模型中制定了告警 相关性的描述语言和规则发现步骤. 基于此,讨论了基于告警相关性分析的通信网故障诊断系统. 最后给出了告 警相关性分析模型在通信网中实现的前提条件和特点. 仿真实验表明,该模型可以压缩冗余告警信息,有利于故障 定位.
dfa_ny
- 给出去趋势分析DFA方法的精确求解,应用于股票数据分析和气象要素场的长程相关性研究-Out trend analysis to the exact solution of DFA method applied to analysis of stock data and meteorological elements of market research and long-range correlation
deep-CCA
- 深度典型相关性分析,在线性的CCA上增加了深度网络,以此来学习新特征并提高多模态数据之间相关性- Deep cca ,the deep network is added in linear CCA to learning descr iption that the correlation is better between multi-modal datas
PCA
- 主成分分析,空间降维的人工智能算法,也能用来去相关性,在图像等信号处理常用-Principal component analysis, spatial dimensionality reduction of artificial intelligence algorithms, but also can come and relevance, in the image signal processing such as common
k_means
- 主成分分析(Principal Component Analysis,PCA), 是一种统计方法。通过正交变换将一组可能存在相关性的变量转换为一组线性不相关的变量,转换后的这组变量叫主成分。(It is a statistical method. Through orthogonal transformation, a set of variables that can be correlated can be transformed into a group of linearly irrel
