Identification of Community Behavior and Sustainable Rural Tourism Based on DWT-ANN Hybrid Model

Abstract

Expanding the tourism infrastructure to rural areas has a positive effect on the local economies. Investment in new attractions and improved infrastructure is necessary to increase rural tourism. A country's economy can benefit from a rise in rural tourism. Tourists flock to these areas as new ideas and places are discovered there. Economic development uses a wide range of ideas and tools to boost growth throughout a country. With greenhouses and other modern takes on rural living, the countryside is once again becoming a tourist destination. Rural tourism growth is facilitated via the application of models and techniques. Three methods preprocessing, feature extraction, and model training form the basis of the suggested strategy. In order to make them comparable to one another, they employed the Zero-unitarization method during preprocessing to replace their unique ranges of variability with a single common range. PCA was utilized for feature extraction. Let's move on to training the models with DWT-ANN. The proposed method is clearly superior than the two most common alternatives, DWT and ANN. There was a 97.23 percent success rate with the recommended method.