Analysis and study on the key factors of regional tourism development based on discrete differential algorithm.

In this paper, a discrete differential algorithm is proposed to extract data features. The strategy of regional tourism development, features extraction and the technology of retaining the subject information of industry characteristic data are analyzed to reduce the feature space dimension and achieve data dimension reduction through the key factors in the development of tourism industry in the region. In this paper, a kind of distributed feature selection system is obtained based on local fisher discriminant according to the feature selection method based on data structure and the feature of modal distribution in industrial characteristic data. The experimental results show that this feature can make the space describe the data distribution structure accurately after dimension reduction. [ABSTRACT FROM AUTHOR]