In the era of big data, the analysis of multi-dimensional time series data is one of the important topics in many fields such as finance, science, logistics, and engineering. Using stacked graphs for visual analysis helps to visually reveal the changing characteristics of each dimension over time. In order to present visually appealing and easy-to-read stacked graphs, this paper constructs the minimum cumulative variance rule to determine the stacking order of each dimension, as well as adopts the width priority principle and the color complementary principle to determine the label placement positioning and text coloring. In addition, a color matching method is recommended by user study. The proposed optimal visual layout algorithm is applied to the visual analysis of actual multidimensional financial time series data, and as a result, vividly reveals the characteristics of the flow of securities trading funds between sectors.

在大数据时代，多维时间序列数据的分析是金融、科学、物流、工程等诸多领域的重要课题之一。使用堆叠图进行可视化分析有助于直观地揭示每个维度随时间变化的特征。为了呈现视觉上吸引人且易于阅读的堆叠图，本文构建了最小累积方差规则来确定每个维度的堆叠顺序，并采用宽度优先原则和颜色互补原则来确定标签放置定位和文字着色。此外，用户研究推荐了一种配色方法。将所提出的最优可视化布局算法应用于实际多维金融时间序列数据的可视化分析，结果，