Tourism Demand Forecasting based on Adaptive Neural Network Technology in Business Intelligence
Year: 2024
Type: article
Abstract: In order to improve the effect of demand forecasting, this paper combines the adaptive neural network technology to construct a demand forecasting model, and proposes an adaptive fault-tolerant PI control strategy for multiple-input and multiple-output systems. In order to verify the effectiveness and stability of the designed adaptive fault-tolerant PI control strategy, this paper uses an iterative algorithm to improve the tracking control accuracy. Moreover, this paper integrates temporal geography with the theory of probabilistic temporal geography, system analysis theory, and tourist flow space-time bayonet theory to propose a research framework for forecasting tourist flow spatio-temporal bayonet based on the WITNESS simulation system. The research shows that the tourism demand forecasting model based on adaptive neural network technology proposed in this paper has good tourism demand forecasting effect, and has a certain effect on promoting the development of tourism.
Source: Computer Fraud & Security
DOI: 10.52710/cfs.140
Author: Jun Li
Institution: Zhengzhou Tourism College
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: bronze
OpenAlex ID: W4406959563