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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,738 papers · 148 categories

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0111 · Jan 202019922001200920172026
3 results for “overheating”
Fault detection in propulsion motors in the presence of concept driftstat.AP

Machine learning monitors detect motor overheating, adapting to concept drift.

problem Early detection of motor overheating in ships' propulsion systems.
method Machine learning and statistical methods using historical data to adapt to concept drift.
result The proposed monitors provide early detection of overheating during and after concept drifts.
machine learningfault detectionconcept driftoverheatingpropulsion motors
2024-06-12abs ↗pdf ↗
Dynamics of Periodic Bubbles and Crashes: Modeling Market Overheating and Panic Selling via Cubic Momentumq-fin.TR

Modeling financial bubbles and crashes with a cubic momentum function.

problem Capturing the micro-level dynamics of investor behavior and panic selling.
method Introducing a cubic function of market momentum to model trend-following and sudden crashes.
result The model successfully replicates complex, nonlinear bubble dynamics.
financial bubblesmarket crashescubic momentumherd behaviorpanic selling
2026-04-21abs ↗pdf ↗
Data-Driven Permanent Magnet Temperature Estimation in Synchronous Motors with Supervised Machine Learningcs.LG

This study evaluates machine learning models for precise temperature estimation in PMSMs.

problem Precise temperature monitoring of PMSMs for automotive applications.
method Evaluation of various machine learning models (ordinary and weighted least squares, support vector regression, k-nearest neighbors, randomized trees, neural networks) on collected data.
result ML models can predict magnet temperature profiles as accurately as classical models, but differ in model size and efficiency.
machine learningtemperature estimationpermanent magnet synchronous motorssupervised learningneural networks
2020-01-17abs ↗pdf ↗