# Long-Short Term Spatiotemporal Tensor Prediction for Passenger Flow Profile

arXiv: https://arxiv.org/abs/2004.11022 · HTML: https://mlsanity.com/paper/2004.11022/

## Key facts

- Cited by 16 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Apr 2020.

## Built on by (most cited first, 16 of 16)

- [Jointly Contrastive Representation Learning on Road Network and Trajectory](https://mlsanity.com/paper/2209.06389/) (2022)
- [KITS: Inductive Spatio-Temporal Kriging with Increment Training Strategy](https://mlsanity.com/paper/2311.02565/) (2023)
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- [Dynamic Causal Graph Convolutional Network for Traffic Prediction](https://mlsanity.com/paper/2306.07019/) (2023)
- [Online Test-Time Adaptation of Spatial-Temporal Traffic Flow Forecasting](https://mlsanity.com/paper/2401.04148/) (2024)
- [Correlated Time Series Self-Supervised Representation Learning via Spatiotemporal Bootstrapping](https://mlsanity.com/paper/2306.06994/) (2023)
- [Adaptive Hierarchical SpatioTemporal Network for Traffic Forecasting](https://mlsanity.com/paper/2306.09386/) (2023)
- [Low-Rank Robust Subspace Tensor Clustering for Metro Passenger Flow Modeling](https://mlsanity.com/paper/2404.04403/) (2024)
- [Choose A Table: Tensor Dirichlet Process Multinomial Mixture Model with Graphs for Passenger Trajectory Clustering](https://mlsanity.com/paper/2310.20224/) (2023)
- [A Critical Perceptual Pre-trained Model for Complex Trajectory Recovery](https://mlsanity.com/paper/2311.02631/) (2023)
- [VisionTraj: A Noise-Robust Trajectory Recovery Framework based on Large-scale Camera Network](https://mlsanity.com/paper/2312.06428/) (2023)
- [Skin Cancer Detection utilizing Deep Learning: Classification of Skin Lesion Images using a Vision Transformer](https://mlsanity.com/paper/2407.18554/) (2024)
- [Deep Causal Learning to Explain and Quantify The Geo-Tension's Impact on Natural Gas Market](https://mlsanity.com/paper/2407.10878/) (2024)
- [Transformer-based Drum-level Prediction in a Boiler Plant with Delayed Relations among Multivariates](https://mlsanity.com/paper/2407.11180/) (2024)
- [Exploring Genre and Success Classification through Song Lyrics using DistilBERT: A Fun NLP Venture](https://mlsanity.com/paper/2407.21068/) (2024)
- [Enabling Tensor Decomposition for Time-Series Classification via A Simple Pseudo-Laplacian Contrast](https://mlsanity.com/paper/2409.15200/) (2024)

## Abstract (arXiv)

Spatiotemporal data is very common in many applications, such as manufacturing systems and transportation systems. It is typically difficult to be accurately predicted given intrinsic complex spatial and temporal correlations. Most of the existing methods based on various statistical models and regularization terms, fail to preserve innate features in data alongside their complex correlations. In this paper, we focus on a tensor-based prediction and propose several practical techniques to improve prediction. For long-term prediction specifically, we propose the "Tensor Decomposition + 2-Dimensional Auto-Regressive Moving Average (2D-ARMA)" model, and an effective way to update prediction real-time; For short-term prediction, we propose to conduct tensor completion based on tensor clustering to avoid oversimplifying and ensure accuracy. A case study based on the metro passenger flow data is conducted to demonstrate the improved performance.