[Establishment of an artificial neural network model for analysis of the influence of climate factors on the density of Aedes albopictus].
OBJECTIVE
To establish a model for predicting the density of Aedes albopictus based on the climate factors.


METHODS
The data of Aedes albopictus density and climate changes from 1995 to 2001 in Guangzhou were collected and analyzed. The predicting model for Aedes albopictus density was established using the Artificial Neural Network Toolbox of Matlab 7.0 software package. The climate factors used to establish the model included the average monthly pressure, evaporation capacity, relative humidity, sunshine hour, temperature, wind speed, and precipitation, and the established model was tested and verified.


RESULTS
The BP network model was established according to data of mosquito density and climate factors. After training the neural network for 25 times, the error of performance decreased from 0.305 539 to 2.937 51x10(-14). Verification of the model with the data of mosquito density showed a concordance rate of prediction of 80%.


CONCLUSIONS
The neural network model based on the climate factors is effective for predicting Aedes albopictus density.
Yu
De-xian
DX
Department of Epidemiology, School of Public Health and Tropical Medicine, Southern Medical University, Guangzhou 510515, China.
Lin
Li-feng
LF
Luo
Lei
L
Zhou
Wen
W
Gao
Lu-lu
LL
Chen
Qing
Q
Yu
Shou-yi
SY
D000330:Aedes / Q000502:physiology*; D000818:Animals; D002980:Climate; D016571:Neural Networks, Computer; D012621:Seasons; D012984:Software