In order to solve problem of failing or false alarm in traditional single sensor type fire detector

multisensor information fusion technology is applied to fire early prediction

it combines temperature

smog concentration and CO concentration together and analyze comprehensively. Extension neural network is used as data fusion algorithm

input values are temperature

smog concentration and CO concentration

and output values are three kinds of fire warning level. Simulation analysis result shows that correct identification rate of fire is in a very high level

which reaches above 93. 9 %. At the same time

compared with traditional BP neural network

it shows that extension neural network has a prominent advantage in speed of data fusion and reliability

so it is possible to apply extension neural network to fire early prediction.