Flow Reconstruction from Sparse Measurements in Urban Drainage Networks: An Application and Evaluation of Data-Driven Sparse Sensing

arXiv:2511.04556 · cs.AI, cs.CE · Submitted 2025-11-06 · Read on arXiv

cs.AI, cs.CE

Submitted: 2025-11-06

Updated: 2026-09-25

Code: https://github.com/DzhZzz/Data-Driven-Sparse-Sensing

Terminology

• Robustness — 18× in this paper · explained in 5 episodes
• Accuracy — 14× in this paper · explained in 1 episode
• Benchmark — 8× in this paper · explained in 2 episodes
• Redundancy — 7× in this paper · explained in 2 episodes
• Singular Value Decomposition — 5× in this paper
• Digital Twin — 3× in this paper · explained in 4 episodes
• Information Gain — 3× in this paper · explained in 2 episodes
• Reinforcement Learning — 3× in this paper · explained in 4 episodes
• Singular Value Decomposition (SVD) — 3× in this paper · explained in 2 episodes
• Clustering — 2× in this paper · explained in 2 episodes
• Fidelity — 2× in this paper · explained in 2 episodes
• Nash-Sutcliffe Efficiency — 2× in this paper
• Abundance — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Calibration — 1× in this paper · explained in 7 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• Data Fusion — 1× in this paper · explained in 3 episodes
• Deep Reinforcement Learning — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Matrix Completion — 1× in this paper · explained in 3 episodes
• Reconstruction Error — 1× in this paper · explained in 2 episodes
• Resource Constraints — 1× in this paper · explained in 3 episodes
• Sparsity — 1× in this paper · explained in 4 episodes
• Transferability — 1× in this paper · explained in 4 episodes

Related papers

• MAVEN-T: Reinforced Heterogeneous Distillation for Real-Time Multi-Agent Trajectory Prediction
• Model Discovery Agent: LLM-assisted Bayesian experiment design for data-efficient discovery of mechanistic world models
• The Clinician's Veto: Navigating Trust, Liability, and Uncertainty in Autonomous AI Prescribing
• MindHelper: Closed-Loop Embodied Mental-State Reasoning for Precision Intervention
• Incumbent Advantage: Brand Bias and Cognitive Manipulation Dynamics in LLM Recommendation Systems
• VSAL: A Vision Solver with Adaptive Layouts for Graph Property Detection