Hyperband-Optimized CNN-BiLSTM with Attention Mechanism for Corporate Financial Distress Prediction

Hyperband-Optimized CNN-BiLSTM with Attention Mechanism for Corporate Financial Distress Prediction

In the context of new quality productive forces, enterprises must leverage technological innovation and intelligent management to enhance financial risk resilience. This article proposes a financial distress prediction model based on deep learning, combined with a CNN, BiLSTM, and attention mechanis...

Full description

Saved in:
Bibliographic Details
Main Authors: Yingying Song, Monchaya Chiangpradit, Piyapatr Busababodhin
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Applied Sciences
Subjects:
financial distress
hyperband algorithm
convolutional neural networks
bidirectional long short-term memory
attention mechanism
Online Access:https://www.mdpi.com/2076-3417/15/11/5934
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://www.mdpi.com/2076-3417/15/11/5934

Similar Items