CEOSRL

Citation Author(s):
Jingyang
Chen
Submitted by:
Jingyang Chen
Last updated:
Wed, 04/03/2024 - 03:47
DOI:
10.21227/nm22-jx64
License:
0
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Abstract 

The uploaded project is the code and dataset for Charging Efficiency Optimization Based on Swarm Reinforcement Learning under Dynamic Energy Consumption for WRSN. The details of each document in the uploaded project are as follows. Document data: The data file contains network data and simulation data. Document iostream: The iostream file contains the program for reading data and writing data. Document main: The main file contains the main program that executes the simulation. Document network: The network file contains the operation programs of individual parts of the WRSN in simulation. Document optimizer: The optimizer file contains the programs for executing different optimization schemes in the simulation.

Instructions: 

The project includes code and dataset and is developed with Python. See README.docx for details within the file.