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BP neural network specifications

Information


Unique identifier OMICS_27200
Name BP neural network
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages R
Computer skills Advanced
Stability Stable
Maintained Yes

Versioning


No version available

Maintainer


  • person_outline Qi Guo

Publication for BP neural network

BP neural network citations

 (172)
library_books

Blood hyperviscosity identification with reflective spectroscopy of tongue tip based on principal component analysis combining artificial neural network

2018
Biomed Eng Online
PMCID: 5946417
PMID: 29747693
DOI: 10.1186/s12938-018-0495-3

[…] e unknown sample is classified as healthy subject; if the output vector approximates to − 1, the unknown sample is classified as hyperviscosity subject. In this paper, a three-layer back-propagation (BP) neural network is used. According to empirical formula, the optimal number of neurons in hidden layer is determined by n+m+a []. Here, n is the number of the input layer neurons, namely, equal to […]

library_books

Attentional Bias in Human Category Learning: The Case of Deep Learning

2018
Front Psychol
PMCID: 5909172
PMID: 29706907
DOI: 10.3389/fpsyg.2018.00374

[…] ried, but see footnote 1 for more details; Hanson and Gluck, ; Kruschke, ; Kurtz, ). That is, the BP network failed to categorize in the way humans do. This result shed doubt on the usefulness of the BP neural network and neural networks more generally as an adequate model for human attentional bias. This result consequently caused researchers to turn to various modifications of BP networks in the […]

library_books

Recognition of Broken Wire Rope Based on Remanence using EEMD and Wavelet Methods

2018
PMCID: 5948680
PMID: 29621174
DOI: 10.3390/s18041110

[…] In this paper, a BP neural network was used to train a classifier that could export the number of broken wires. After extracting the features of a defect image, a three-layer BP neural network was trained to identify […]

library_books

Influence of Vehicle Speed on the Characteristics of Driver’s Eye Movement at a Highway Tunnel Entrance during Day and Night Conditions: A Pilot Study

2018
PMCID: 5923698
PMID: 29614793
DOI: 10.3390/ijerph15040656

[…] tunnel entrance is much lower than inside of the tunnel. Zhao et al. [] used nine drivers to study visual information perception and variation during daytime and simulated visual feature variation by BP Neural Network. The experimental data of this study showed that fixation duration and saccade amplitude decreased gradually before tunnel entrance and increased first after entering the entrance an […]

library_books

Prediction of influenza like illness based on the improved artificial tree algorithm and artificial neural network

2018
Sci Rep
PMCID: 5861130
PMID: 29559649
DOI: 10.1038/s41598-018-23075-1

[…] First, we use the basic BP neural network for prediction to revise some missing data. We perform ten times and take the corresponding prediction of the missing data with the minimum MAPE. For example, The Twitter data for re […]

library_books

Ontology Based Method for Fault Diagnosis of Loaders

2018
PMCID: 5876616
PMID: 29495646
DOI: 10.3390/s18030729

[…] ng the production process knowledge of workshops based on the IDEF5 method which has disadvantages in technical support. Zhou Yong [] constructed an improved ontology model based on machine learning (BP neural network) which changed the mode of multi strategy merging in ontology mapping. S. Chaware et al. [] integrated METHONTOLOGY and SENSUS to construct an ontology model for the shopping mall do […]

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BP neural network institution(s)
Health Science Center, Peking University, Peking, China; Department of Mathematics, Harbin Institute of Technology, Harbin, China
BP neural network funding source(s)
Supported by the Fundamental Research Funds for the Central Universities and Program for Innovation Research of Science in Harbin Institute of Technology (No. GFQQ5750001516).

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