Analyzing the impact of El Nilo Southern Oscillation (ENSO) on the number of tourists is essential in realizing the sustainable development of natural scenic spots. From the current research results, research on the effects of ENSO on tourism focuses on the impact of the formation of the natural environment. However, there is a lack of ENSO-related research on the number of people arriving at natural attractions. This paper considers the adjustment effects of personal disposable income, per capita GDP, and population size and constructs a new framework of ENSO’s influence on tourism. This paper builds a system GMM (Gaussian Mixture Model) and analyzes the impact of ENSO on tourist flow by using Google Trend data (big data technology) to obtain annual passenger flow data of 48 natural scenic spots in the United States (mainly national parks and national forests). The empirical results show that the increase in ENSO has led to a significant decrease in visitors to natural attractions in the United States. Moreover, the increase in personal disposable income, per capita GDP, and population size can weaken the relationship between ENSO and the number of tourists. This research expands and enriches the theoretical perspective of ENSO and outdoor tourism.

To address issues involving inconsistencies, this paper proposes a stochastic multi-criteria group decision making algorithm based on neutrosophic soft sets, which includes a pair of asymmetric functions: Truth-membership and false-membership, and an indeterminacy-membership function. For integrating an inherent stochastic, the algorithm expresses the weights of decision makers and parameter subjective weights by neutrosophic numbers instead of determinate values. Additionally, the algorithm is guided by the prospect theory, which incorporates psychological expectations of decision makers into decision making. To construct the prospect decision matrix, this research establishes a conflict degree measure of neutrosophic numbers and improves it to accommodate the stochastic multi-criteria group decision making. Moreover, we introduce the weighted average aggregation rule and weighted geometric aggregation rule of neutrosophic soft sets. Later, this study presents an algorithm for neutrosophic soft sets in the stochastic multi-criteria group decision making based on the prospect theory. Finally, we perform an illustrative example and a comparative analysis to prove the effectiveness and feasibility of the proposed algorithm.