Prediction and optimization of tourists’ spatial-temporal behavior during peak period in scenic spots: a simulation-based analysis

Tourists’ spatial-temporal behavior has complex and dynamic randomness, which affects the intelligent management of scenic spots. Understanding mastering tourists within peak period spots is one key means to improving competitiveness enhancing tourism satisfaction. This paper explores how effectively optimize tourists’ improve overall efficiency Firstly, we built a simulation model found transfer change law between attractions through historical data. Then, predicted distribution number their subsequent selected minimum load attraction as next destination for tourists. Finally, experiment proves that selection optimization based on individual tourist can balance spot alleviate congestion level.