Analyzing intelligent tourism development and public services based on a fuzzy genetic hybrid system to promote environmental and cultural values

Abstract

Environmental, cultural, and public service-dependent factors encourage the development of a country’s tourism. In recent years, automated tourism development using statistical and accumulated data has been exploited to recommend attractive tourist features. This article thus discloses an intelligent development assessment method (IDAM) using cumulative factors (CFs) for deriving development-focused improvement in tourism. This method accounts for public services and environmental and cultural factors that promote tourism for better assessment. The fuzzy process identifies the maximum possible impacting factors by independently evaluating the reviewed values. Based on the reviewed values, the manipulation of factor relationships is derived to identify even trivial factors impacting development. The fuzzy outputs are thus integrated with optimistically impacting development factors to provide attractive recommendations. Such recommendations are analyzed using fuzzy data for previous and current development factors for new decisions. The system’s efficiency was evaluated using the recommendation ratio, ensuring a 48.58% success rate, a development rate of 0.105%, a 4-factor detection rate, and a review-based assessment rate of 55.5% for a sample size of 5,000 visitors.