title: [Establishment of an artificial neural network model for analysis of the influence of climate factors on the density of Aedes albopictus].
abstract: 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.
authors.affiliation: Department of Epidemiology, School of Public Health and Tropical Medicine, Southern Medical University, Guangzhou 510515, China.
authors.forename: De-xian
authors.initials: DX
authors.lastname: Yu
authors.forename: Li-feng
authors.initials: LF
authors.lastname: Lin
authors.forename: Lei
authors.initials: L
authors.lastname: Luo
authors.forename: Wen
authors.initials: W
authors.lastname: Zhou
authors.forename: Lu-lu
authors.initials: LL
authors.lastname: Gao
authors.forename: Qing
authors.initials: Q
authors.lastname: Chen
authors.forename: Shou-yi
authors.initials: SY
authors.lastname: Yu
mesh_terms: D000330:Aedes / Q000502:physiology*; D000818:Animals; D002980:Climate; D016571:Neural Networks, Computer; D012621:Seasons; D012984:Software