Intelligent Algorithm Enabling High Quality Development of Low Altitude Economy

In recent years, with the rise of the drone industry, the development of the low-altitude economy has become increasingly prosperous. As an important part of the new quality productivity, the low-altitude economy has a broad development space and market prospects. However, the development of the low-altitude economy has been hindered to a certain extent due to factors such as incomplete infrastructure. Therefore, this study explores the horizontal composition analysis and vertical development path of the low-altitude economy. In terms of horizontal composition analysis, the development factors are analyzed by the clustering and entropy weight method, and the horizontal prediction of the scale of low-altitude economy is achieved based on multiple linear regression and neural network algorithms. In the vertical development path investigation, the accurate prediction of low-altitude economy development is achieved by constructing a multivariate LSTM time series model, and the growth rate correlation analysis is carried out by combining the elements of the low-altitude economy and the total revenue of the low-altitude economy, which reveals the intrinsic development correlation between the elements and the total revenue.