Optimization Analysis of Higher Mathematics Resources Based on Convolution Neural Network Algorithm

Convolution neural network is an artificial intelligence algorithm. It is an algorithm that can be used to solve problems in the field of mathematics. Convolution neural networks have been used to solve optimization problems, such as finding the minimum, maximum or the optimal solution of a given problem. Convolution neural networks have been used to find solutions to optimization problems, such as finding the minimum, maximum or the optimal solution of a given problem. This method was developed by LeCun et al. (1986). There are many ways to recommend advanced mathematics resources, but some algorithms have problems and defects, and the final recommendation results are not reliable and accurate. Therefore, a resource recommendation algorithm for advanced mathematics based on convolution neural network is proposed. Set the weighted fuzzy resource recommendation target, determine the level of collaborative convolution mathematical resource recommendation, construct the convolution neural network mathematical resource recommendation model, and realize the design of advanced mathematical resource recommendation algorithm through the membership matrix. The experimental results show that compared with the traditional fuzzy hierarchical mathematical resource recommendation algorithm test group, the final MSE mean value of the convolutional neural network mathematical resource recommendation algorithm test group designed in this paper is relatively high, indicating that this algorithm has better application accuracy and reliability, and has practical application value.