The paper surveys EV charging literature through a Planning-Scheduling-Behavior framework and diagnoses a fidelity-tractability trilemma in cross-layer integration.
Credit default prediction of Chinese real estate listed companies based on explainable machine learning
2 Pith papers cite this work. Polarity classification is still indexing.
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AI adoption proxies from text and patents improve out-of-sample distress prediction in Chinese firms when machine learning models use temporally pruned recent training windows.
citing papers explorer
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Planning, Scheduling, and Behavior in EV Charging Systems: A Critical Survey and Trilemma Framework
The paper surveys EV charging literature through a Planning-Scheduling-Behavior framework and diagnoses a fidelity-tractability trilemma in cross-layer integration.
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Forecasting financial distress in dynamic environments AI adoption signals and temporally pruned training windows
AI adoption proxies from text and patents improve out-of-sample distress prediction in Chinese firms when machine learning models use temporally pruned recent training windows.