DDPG with Transfer Learning and Meta Learning Framework for Resource Allocation in Underlay Cognitive Radio Network

In the context of the wide application of big data technology, it is particularly important to optimize the allocation of teaching methods and learning resources. This study first expounds the key role of big data in the optimization of teaching methods and the allocation of learning resources, and emphasizes how big data technology promotes the transformation and development of education and teaching models. Based on the analysis of traditional models of teaching method optimization and learning resource allocation, this study proposes a new model driven by big data. By accurately identifying students’ learning needs and behavior patterns, the model optimizes teaching methods and allocation of learning resources. This study introduces the whole process of data collection, cleaning, analysis and modeling. In the process, it shows how big data can be integrated, analyzed, and applied to further support the construction and validation of models. Through empirical research and effect evaluation, this study proves the validity of the model of teaching method optimization and learning resource allocation driven by big data, and demonstrates how big data can promote educational equity and improve educational quality.

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DDPG with Transfer Learning and Meta Learning Framework for Resource Allocation in Underlay Cognitive Radio Network

Cited by 2 publications

References 37 publications

Underlay Cognitive Radio Resource Management with Hybrid Meta-Loss Learning

Underlay Cognitive Radio Resource Management with Hybrid Meta-Loss Learning

Optimization of teaching methods and allocation of learning resources under the background of big data

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