What question did this study set out to answer?

To establish a big-data-driven evaluation and management framework that resolves structural imbalances between idle and scarce higher education resources.

August 16, 2026Advanced ElectromagneticsOpen Access

Evaluation and Management Optimization of Higher Education Resource Allocation Efficiency Driven by Big Data

View Full Paper

Ask AI

Bookmark

Authors

DLD. H. Liang XDX. Y. Dong CBC. Bai

Discussion

Member takes

Implication

Computational modeling study demonstrates dynamic optimization of higher education resource allocation, suggesting significant efficiency gains via reinforcement learning.

Key Points

To establish a big-data-driven evaluation and management framework that resolves structural imbalances between idle and scarce higher education resources.
Integrated human, financial, material, and information resource inputs using multi-source data acquisition and preprocessing.
Evaluated intertemporal efficiency using a dynamic network SBM-DEA model and extracted spatiotemporal trends using STL decomposition, spatial clustering, and LSTM networks.
Constructed a closed-loop management intervention framework using a Deep Q-Network reinforcement learning algorithm.
The median resource demand response lag decreased from 17.65 h in 2018 to 10 h in 2023.
The strategy adoption conversion rate improved from 0.551 to 0.861.

Cite This Study

Liang et al. (2026) studied this question.

synapsesocial.com/papers/6a817a4cf2fb91fc834ae089 https://doi.org/10.7716/aem.v15i3.3428

View Full Paper

Ask AI

Bookmark

Implication

Computational modeling study demonstrates dynamic optimization of higher education resource allocation, suggesting significant efficiency gains via reinforcement learning.

Evaluation and Management Optimization of Higher Education Resource Allocation Efficiency Driven by Big Data

Discussion

Member takes

Implication

Key Points

Cite This Study

Evaluation and Management Optimization of Higher Education Resource Allocation Efficiency Driven by Big Data

Discussion

Member takes

Implication

Key Points

Cite This Study

Also Consider

Also Consider