Artificial Intelligence Prediction and Decision Evaluation Model Based on Deep Learning

Abstract

Under the active promotion of major countries in the world, the integration of AI and many fields has continued to deepen, and a series of new technologies, new formats and new models have emerged. The application of artificial intelligence algorithm for machine learning, to help government departments and institutions predict information related to the future, to provide decision-making advice. Based on the relevant data of the talent market in A city, this paper analyzes the supply and demand situation of local talents. The data is processed using wavelet threshold denoising and a NAR neural network model is established for prediction. Taking employment satisfaction, Chinese student employment rate and average salary as indicators, combined with GM (1,1) forecasting model to predict employment situation. The SOM neural network model is established based on the number of applicants, academic requirements, the number of students admitted, and the fast-growing industry in the A city. Finally, the paper compares the characteristics of the above-mentioned indicators in A city with other cities in China, and matches other cities with the same characteristics as the city A, and builds an "intelligent forecasting and decision-making evaluation model" to help government departments and related institutions predict future urban development.