Sensor data classification method based on Stack integrated neural network

The invention discloses a sensor data classification method based on a Stack integrated neural network, and the method comprises the steps: 1) constructing a basic learner which comprises a feature extraction unit and a feature classification unit connected with the feature extraction unit, 2) takin...

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Hauptverfasser: YI LIN, QIAN JUNHUI, LIU RAN, WANG MINGXUE, CUI SHANSHAN, TIAN FENGCHUN, LIU YAQIONG, ZHENG YANGTING, WANG FEIFEI, CHEN XI, ZHAO YANG
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creator YI LIN
QIAN JUNHUI
LIU RAN
WANG MINGXUE
CUI SHANSHAN
TIAN FENGCHUN
LIU YAQIONG
ZHENG YANGTING
WANG FEIFEI
CHEN XI
ZHAO YANG
description The invention discloses a sensor data classification method based on a Stack integrated neural network, and the method comprises the steps: 1) constructing a basic learner which comprises a feature extraction unit and a feature classification unit connected with the feature extraction unit, 2) taking outputs of a plurality of basic learners as inputs of meta learners, and constructing a Stacking model, and 3) simultaneously inputting the sensor data into a one-dimensional convolution layer of each feature extraction unit of each basic learner, taking the output of each basic learner as the input of a meta-learner of the Stacking model, processing the sensor data by the meta-learner, and outputting a final classification result by a softmax function layer of the meta-learner. According to the method, the advantages of the convolutional neural network and the long-term and short-term memory network for extracting the sensor data features are combined, the accuracy of sensor data classification is improved, and
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subjects CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
HANDLING RECORD CARRIERS
PHYSICS
PRESENTATION OF DATA
RECOGNITION OF DATA
RECORD CARRIERS
title Sensor data classification method based on Stack integrated neural network
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