对时间序列预测和分类的时空图形神经网络模型进行系统的文献综述
Flavio Corradini1, Flavio Gerosa1, Marco Gori2
1School of Science and Technology, University of Camerino, via Madonna delle Carceri 9, Camerino, 62032, Italy.
概括
本系统性综述探讨了用于时间序列分析的时空图形神经网络 (GNN). 它提供了对这个快速发展的领域的模型,应用和挑战的全面概述.
科学领域:
- 人工智能的人工智能
- 机器学习 机器学习
- 数据科学数据科学数据科学
背景情况:
- 时空图神经网络 (GNN) 越来越多地用于时间序列分析.
- GNN擅长捕捉跨变量和时间的复杂依赖关系.
研究的目的:
- 在时间序列分类和预测中提供GNN的综合系统文献综述.
- 整合关于模型,数据集,基准和结果的信息.
主要方法:
- 系统的数据库搜索.
- 选择和详细审查366篇相关的研究论文.
- 分析当前最先进的模型和应用.
主要成果:
- 详细概述时空GNN模型及其应用领域的详细概述.
- 资源的编译,包括源代码,数据集和基准结果.
- 确定GNN模型在不同领域的结果的首次广泛比较.
结论:
- 时空GNN对时间序列分析具有显著的前景.
- 关键的挑战包括可比性,可重现性,可解释性,信息容量和可扩展性.
- 该综述旨在通过提供综合资源和突出未来研究方向来帮助研究人员.
相关概念视频
00:54Time-Series Graph
5.0K
A time-series graph is a line graph with repeated measurements taken at successive intervals of time. It is also called a time series chart. To construct a time-series graph, one must look at both pieces of a paired data set. The horizontal axis is used to plot the time increments, and the vertical axis is used to plot the values of the variable that one is measuring. By using the axes in this way, each point on the graph will correspond to time and a measured quantity. The points on the graph...
5.0K
01:26Classification of Systems-I
543
Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
543
01:31Classification of Systems-II
447
Continuous-time systems have continuous input and output signals, with time measured continuously. These systems are generally defined by differential or algebraic equations. For instance, in an RC circuit, the relationship between input and output voltage is expressed through a differential equation derived from Ohm's law and the capacitor relation,
447
01:25Selected Data About Geographic Locations
249
Geographic Information Systems (GIS) rely on two core types of data: spatial data and attribute data.Spatial DataSpatial data defines the physical location of features within a coordinate system, typically expressed in terms of latitude and longitude. It provides precise positioning for elements like roads, rivers, or buildings.Attribute DataAttribute data complements spatial data by adding descriptive information about these features. For example, a road's spatial data includes its start and...
249
01:30Classification of Signals
1.3K
In signal processing, signals are classified based on various characteristics: continuous-time versus discrete-time, periodic versus aperiodic, analog versus digital, and causal versus noncausal. Each category highlights distinct properties crucial for understanding and manipulating signals.
A continuous-time signal holds a value at every instant in time, representing information seamlessly. In contrast, a discrete-time signal holds values only at specific moments, often denoted as x(n), where...
A continuous-time signal holds a value at every instant in time, representing information seamlessly. In contrast, a discrete-time signal holds values only at specific moments, often denoted as x(n), where...
1.3K