Accesso libero

An Optimization Model of Financial Management Teaching Strategies Based on Reinforcement Learning

Fei Wang

Fei Wang

School of Economic Management, Daqing Normal UniversityDaqing, China
Cerca questo autore su
Sciendo|Google Scholar
Wang, Fei
  
17 mar 2025
An Optimization Model of Financial Management Teaching Strategies Based on Reinforcement Learning's Cover Image
INFORMAZIONI SU QUESTO ARTICOLO
Articolo precedente
Articolo Successivo
Cita
Scarica la copertina
Pubblicato online: 17 mar 2025
Ricevuto: 17 ott 2024
Accettato: 26 gen 2025
DOI: https://doi.org/10.2478/amns-2025-0233
Parole chiave
© 2025 Fei Wang, published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.

Figure 1.

Basic reinforcement learning framework
Basic reinforcement learning framework

Figure 2.

GRU internal structure
GRU internal structure

Figure 3.

Status indicates the structure of the model
Status indicates the structure of the model

Figure 4.

Structure of decision model
Structure of decision model

Figure 5.

Overall architecture of the course recommendation learning platform system
Overall architecture of the course recommendation learning platform system

Figure 6.

Different models are trained in 1M data sets
Different models are trained in 1M data sets

Figure 7.

The recommended accuracy of various models in different size data sets
The recommended accuracy of various models in different size data sets

Figure 8.

The reward curve of the teaching recommendation platform
The reward curve of the teaching recommendation platform

Figure 9.

The teaching results of the teaching recommendation platform
The teaching results of the teaching recommendation platform

Figure 10.

Recommendations for financial management teaching data
Recommendations for financial management teaching data

Financial management teaching systematically can test the results

Project CPU occupancy rate Memory occupancy rate Mean response time
Application server 26.35% 45.77% 267ms
Algorithm server(unrun) 17.62% 14.96%
Algorithm server(run) 49.15% 53.82%
Lingua:
Inglese
Frequenza di pubblicazione:
1 volte all'anno
Argomenti della rivista:
Scienze biologiche, Scienze della vita, altro, Matematica, Matematica applicata, Matematica generale, Fisica, Fisica, altro
Feed RSS della rivista