基于深度学习机制的火警协议智能分析模型

doi:10.16180/j.cnki.issn1007-7820.2019.01.0017

Abstract

Abstract:

The automatic fire alarm had many brands and models, The data protocols of different brands or models were not the same, which made it difficult for information integration of smart fire.To solve the problem,this paper presented a SSAESMFA model that combined deep learning technology with Fire protocol intelligent analysis model.The model based on stack sparse auto encoder and softmax regression,provided the identification of unknown protocol data through deep learning of known protocol data of fire equipment.After training, The accuracy of SSAESMFA in identifying fire alarm protocol was 99.83%, Experiments showed that the model had a high feature extraction and classification ability of fire equipment protocol data,effectively improved the efficiency of information integration of smart fire.

Key words: automatic fire alarm, intelligent analysis, deep learning, auto encoder, Softmax regression, feature extraction

CLC Number:

TP183

SHI Ce,QIU Jiong. The Fire Protocol Intelligent Analysis Model Based on Deep Learning[J].Electronic Science and Technology, 2019, 32(1): 80-85.

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References 16

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训练次数	SSAESM决策准确率/%	BP神经网络决策准确率/%
20	95.44	87.65
40	98.95	88.10
60	99.53	88.94
80	99.65	89.48
100	99.81	90.34
120	99.83	91.03

训练次数	SSAESMFA训练误差
20	0.062 5
40	0.019 2
60	0.013 4
80	0.004 8
100	0.004 0
120	0.001 6

The Fire Protocol Intelligent Analysis Model Based on Deep Learning

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