An algorithm of fire situation information perception using fuzzy neural network
Wei Shouming, Jiaqi Lu, Chenguang He, Shuai Han · 2021
With the development of mobile communication and information technology, many complex scenes that are difficult for front-line personnel to work have been improved with the support of new technologies. Sensors with more complete functions provide richer communication data, and technological developments such as heterogeneous networks also provide a better communication environment for the field and command center. In a more complex communication scenario such as fire, more abundant communication resources are used to conduct situational awareness on the scene. This paper proposes a fire situation information perception algorithm based on fuzzy neural network. The algorithm normalizes situation information data matrix and trains it as the input of fuzzy neural network. Finally, the fuzzy logic system theory and BP neural network are combined to obtain a fuzzy neural network with good perception of on-site situation information, which provides support for the subsequent decision-making of the command center and front-line personnel.