  To improve the problem that the parameter identification for fuzzy neural
network has many time complexities in calculating, an improved T-S fuzzy
inference method and an parameter identification method for fuzzy neural
network are proposed. It mainly includes three parts. First, improved fuzzy
inference method based on production term for T-S Fuzzy model is explained.
Then, compared with existing Sugeno fuzzy inference based on Compositional
rules and type-distance fuzzy inference method, the proposed fuzzy inference
algorithm has a less amount of complexity in calculating and the calculating
process is simple. Next, a parameter identification method for FNN based on
production inference is proposed. Finally, the proposed method is applied for
the precipitation forecast and security situation prediction. Test results
showed that the proposed method significantly improved the effectiveness of
identification, reduced the learning order, time complexity and learning error.
