An ecological health evaluation of tourist attractions based on gradient boosting decision tree

In order to overcome many problems existing in traditional evaluation methods, such as the low accuracy of the evaluation of ecological health of tourist attractions, an ecological health evaluation method of tourist attractions based on gradient boosting decision tree was proposed. The data collection framework of tourist attractions based on UAV low-altitude remote sensing is designed, the ecological health evaluation index system of tourist attractions is constructed, and information entropy and analytic hierarchy process were used to determine the combination weight. The gradient boosting decision tree algorithm is used to calculate the ecological health of tourist attractions, and multiple support vector machines are used to construct multi-classifiers to achieve ecological health evaluation. The experimental results show that the average data acquisition time of the method in this paper is 0.76 s, the error rate of the index weight calculation is between -1% and 2%, and the average evaluation accuracy rate is 97.2%.