Deep Integration System of English Information Education(EIE) Based on RBF Algorithm

A perfect EIE and teaching system is composed of an efficient, sensitive, dynamic and innovative information technology platform, hard conditions and optimized soft conditions such as high-quality manpower, intelligence and perseverance. In the information network environment, in order to effectively promote the deep integration of EIE, a new teaching development path is needed to carry and lead. Therefore, this paper proposes the research on the deep fusion system of EIE based on RBF algorithm, discusses and analyzes the RBF neural network learning algorithm, information fusion technology and the fusion point of English education in information teaching, and analyzes the RBF neural network algorithm. In order to verify the teaching effect of the deep integration system of EIE based on RBF algorithm, this paper compares the EIE proposed in this paper with the traditional education mode, investigates the students' evaluation of learning English under the two modes, and tests the students' autonomous learning ability under English information teaching; The results showed that only 59% of the students said that under the traditional English education, their self-reflection ability was improved, while the EIE reached 88%. 84% of the students said that the EIE was helpful to improve their English reading ability, while the traditional education was only 66%; 45.72% of students like to explore independently, but their ability is poor; There are different ways to solve difficulties in learning. Therefore, the deep integration of EIE based on RBF algorithm is helpful to improve students' autonomous learning ability. The improvement of learning ability still needs time to prove. However, it can also prove that the teaching effect of the deep integration system of EIE based on RBF algorithm is worthy of application.