Abstract: In view of the demand for efficient and accurate prediction of the fire in the engine room of the ship, this paper establishes a ship fire prediction method based on the LSTM neural network and decision tree decision. Firstly, it determines three kinds of sensors to collect the fire characteristics of the ship. Secondly, it constructs the LSTM neural network model and optimizes the parameters. The probability of open fire, smoldering fire, no fire and smoke duration output by STM neural network are the inputs of decision tree, and the fire prediction results are output. The typical data of national standard fire are used for training, and experiments are conducted to predict the fire in the engine room of the ship. The experimental results show that the prediction accuracy is over 97% compared with other algorithms. The scheme can effectively predict engine room fire and provide scientific basis for ship safety.

Key words: marine engine room fire, LSTM - ID3, fire detection