Semantic Analysis based on Artificial Intelligence – Prediction of Telecom Fraud

Due to the complexity and diversity of telecom fraud, some current technologies can achieve better results under certain circumstances, but there are still limitations. Therefore, this paper hopes to combine the characteristics of telecom fraud, mining the correlation information between users in order to identify telecom fraud users. An activation function is a significant basic model in a neural network, and its existence makes neural networks have strong expression ability. An activation function is essentially some nonlinear function. After mapping the activation function, the output of neurons is called the activation value. This paper studies the intelligent prediction technology of telecom fraud based on algorithm recognition. The activation function adjusts the prediction range to achieve the desired effect.