Optimization of Sensor Layout for Accurate Fire Localization Using LSTM Models-Reference-Cited by-同舟云学术

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Optimization of Sensor Layout for Accurate Fire Localization Using LSTM Models

Published:2023-09-15 Issue: Volume: Page:
ISSN:
Container-title:2023 2nd International Conference on Artificial Intelligence and Computer Information Technology (AICIT)
language:
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Author:

Zhang Lu¹,Fan Cheng²,Wang Xinghua³,Huang Bufu³

Affiliation:

1. College of Civil and Transportation Engineering, Shenzhen University,Shenzhen,China

2. College of Civil and Transportation Engineering, Shenzhen University,Key Laboratory for Resilient Infrastructures of Coastal Cities, Ministry of Education,Shenzhen,China

3. eSight Technology (Shenzhen) Company Limited,Shenzhen,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10275801/10277698/10277935.pdf?arnumber=10277935

Reference10 articles.

1. Fundamentals of Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) network

2. Using fire dynamic simulation (FDS) to reconstruct an arson fire scene

3. Robustness testing framework for RUL prediction Deep LSTM networks

4. A Dual‐Function Sensor for Highly Sensitive Detection of Flame and Humidity

5. The big picture on the internet of things and the smart city: a review of what we know and what we need to know

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