Neural network-based intelligent fusion terminal testing method

Tao Du

doi:10.1117/12.3035221

7 August 2024 Neural network-based intelligent fusion terminal testing method

Tao Du

Proceedings Volume 13224, 4th International Conference on Internet of Things and Smart City (IoTSC 2024); 1322423 (2024) https://doi.org/10.1117/12.3035221
Event: 4th International Conference on Internet of Things and Smart City, 2024, Hangzhou, China

Abstract

Intelligent fusion terminals are the core components of intelligent distribution stations in low-voltage distribution Internet of Things. To enhance the practical application of intelligent fusion terminals in distribution Internet of Things, a neural network-based intelligent fusion terminal testing method is proposed. The focus is on the neural network-based intelligent fusion terminal testing method and the construction of a neural network model based on modified incentive functions to support communication protocol recognition between intelligent fusion terminals and different devices, improving the detection efficiency of intelligent fusion terminals.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Tao Du "Neural network-based intelligent fusion terminal testing method", Proc. SPIE 13224, 4th International Conference on Internet of Things and Smart City (IoTSC 2024), 1322423 (7 August 2024); https://doi.org/10.1117/12.3035221

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available