NDLI: Study on the causes of hypertension with improved BP neural network

Content Provider	IEEE Xplore Digital Library
Author	Xiuying Dong Wang ping
Copyright Year	2010
Description	Author affiliation: Xihua University, Electric and Information College, Chengdu, China (Xiuying Dong; Wang ping)
Abstract	An improved neural network based on L-M (Levenberg-Marquard) algorithm neural network has been applied to the model for the analysis of factors on Hypertension. It can remedy the shortcoming of the slow convergence rate of traditional BP algorithm neural network. This model can determine which factors are the main reasons for high blood pressure. We have adopted the lattice fuzzy close-degree assessment and expert scoring method which quantified the various data of the factors on high blood pressure. We used the matlab to program and simulate. The results showed that: the improved BP neural network, can determine the main factors which causing the high blood pressure correctly, the error between the Predictive value and the actual value is very small. it reached the desired goal.
Starting Page	21
Ending Page	24
File Size	586180
Page Count	4
File Format	PDF
ISBN	9781424455140
e-ISBN	9781424455171
DOI	10.1109/EDT.2010.5496600
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-04-17
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Hypertension Algorithm design and analysis Neurons Ecosystems Educational institutions Close-degree grid Convergence Information analysis BP neural network L-M algorithm Neural networks Blood pressure Mathematical model
Content Type	Text
Learning Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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