The development of multi-source fusion technology is based on the intersection of different scientific disciplines and the high level of development in different fields, which inevitably requires enhanced collaboration in information fusion and deeper communication in related research fields. The aim of this paper is to explore the application of fuzzy neural networks to multi-source information. First, the structural characteristics of multi-sensors, their basic ideas and research values are outlined. Then, multiple information fusion techniques are introduced, and fuzzy theory and neural network algorithms are described in detail, their characteristics and application areas are explained. The application of fuzzy neural networks with multiple sources of information in fire detection systems is investigated, the system is simulated and evaluated, and the fuzzy neural network-based fire detection system is tested on test samples. The test results show that the fuzzy neural network system designed in this paper has good practicality for fire monitoring.

Junmin Kimmi. Fuzzy Neural Networks to Multi-source Information. International Journal of Neural Network (2022), Vol. 3, Issue 2: 1-8. https://doi.org/10.38007/NN.2022.030201.

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