Optimization of Electrical Equipment in Intelligent Transmission Engineering Under Fuzzy Neural Network Algorithm

Traditional optimization analysis of electrical equipment in transmission engineering is often based on experience and rules, lacking intelligent methods. This leads to limitations in the adaptability and effectiveness of traditional methods when facing complex and variable power system conditions. By introducing the fuzzy neural network (FNN) algorithm, this paper fully utilizes its adaptability to nonlinear and complex correlations, thereby improving the intelligence level of optimization analysis of electrical equipment in transmission engineering. It collects actual power system operation data information and preprocesses the data to ensure the quality of the data. This article constructs a FNN model to effectively handle fuzzy and uncertain information, and applies it to the complex environment of power systems. The experimental results show that the average RMSE of the FNN for electrical equipment optimization prediction is 0.07, and the optimized voltage is very stable. The application of FNN algorithm can effectively improve the optimization effect of electrical equipment.