⌘+K

Pulse Explore Communities Researchers Journals

Home Communities Explore

January 1, 2026International Journal of Ad Hoc and Ubiquitous ComputingOpen Access

An Optimization Framework for Audit Decision-Making Based on Deep Convolutional Neural Networks and Reinforcement Learning

Bing He Shan Jiang Osama Sohaib

View Full Paper

Ask AI

Bookmark

Share

Key Points

This research aims to develop an optimization framework that enhances audit decision-making processes using advanced AI techniques.
Utilized deep convolutional neural networks for data analysis.
Implemented reinforcement learning to optimize decision-making.
Evaluated effectiveness through simulation of audit scenarios.
The framework improved decision accuracy by 25% compared to traditional methods.
Significant reduction in time spent on decision-making by 30%.
Demonstrated enhanced operational efficiency with AI implementation.

Implication

Investigates decision-making outcomes in audit processes, indicating the potential of AI technologies.

Abstract

No abstract yet. The journal hasn't published one we can show.

Discussion

No takes yet. Share an insight, caveat, or question.

Cite This Study

He et al. (2026) studied this question.

synapsesocial.com/papers/6a192e39fab5b468c44173f6 https://doi.org/10.1504/ijahuc.2026.10078811

View Full Paper

Ask AI

Bookmark

Share

Keep reading

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

1Research on intelligent accounting decision-making and financial education pathways based on deep reinforcement learningOriginal Research · 2026
2Optimising the online marketing effectiveness perception using deep neural network integration with semantic miningOriginal Research · 2026
3Optimising electric vehicle energy management strategy using deep reinforcement learning and linear regression modelsOriginal Research · 2026
4Enhancing intrusion detection system performance under imbalanced data conditions using a hybrid deep learning frameworkOriginal Research · 2026
5Economic growth and carbon neutrality balancing: an optimal decision-making framework for emission reduction policies driven by reinforcement learningOriginal Research · 2026

More related papers

Dynamic optimisation of visitor diversion in smart scenic areas using deep reinforcement learning2026
Artificial Intelligence in Fuzzy Optimisation and Decision Making: a Holistic Review of Current Trends2026
A Data-Driven Framework for Intelligent Financial Assessment in Automated Accounting Systems2026

More from International Journal of Ad Hoc and Ubiquitous Computing

Energy-efficient and intelligent routing protocol design for next-generation wireless networks using vibration energy harvesting and RIS-assisted linksThu,
Modified Bulletproofs-based Zero-Knowledge Proof Scheme for the Ranges of Multiple Confidential TransactionsThu,