DocumentCode :
2871680
Title :
A study on artificial neural networks-based fever patient number forecast
Author :
Mao, Yuming
Author_Institution :
Dept. of Inf. Eng., Shandong Jiaotong Univ., Jinan, China
Volume :
9
fYear :
2010
fDate :
22-24 Oct. 2010
Abstract :
The abstract should summarize the contents of the paper and should contain at least 70 and at most 150 words. It should be set in 9-point font size and should be inset 1.0 cm from the right and left margins. There should be two blank (10-point) lines before and after the abstract. This document is in the required format. The number of fever patient increases in winter, this research aimed at advancing BP neural network´s precision in forecast of fever patient number. The method of forecast of fever patient number was based on double-layers BP neural network. The method was used to predict the fever patient number of Shandong Chest Hospital. The hospital can increase doctor number according to the results. The results of the computer simulation showed that the method was applicable, the average relative tolerance was 8.76%. The BP neural network can be used for forecast of fever patient number.
Keywords :
backpropagation; medical computing; neural nets; BP neural network; Shandong chest hospital; artificial neural networks; fever patient number forecast; Artificial neural networks; Heuristic algorithms; Hospitals; Neurons; Training; Transfer functions; BP neural network; component; fever patient number; prediction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4244-7235-2
Electronic_ISBN :
978-1-4244-7237-6
Type :
conf
DOI :
10.1109/ICCASM.2010.5623061
Filename :
5623061
Link To Document :
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