Green Development Evaluation of Tourism Integration Industrial Cluster under the Concept of Sustainable Development

In order to realize the reliable detection of the cultural and tourism integration industry cluster under the concept of sustainable development, the green development evaluation of the tourism integration industry cluster under the concept of sustainable development is proposed. The study creates a big data parameter collection model for the green development evaluation of a cluster in the cultural tourism industry, groups the data into feature groups, produces a model to detect structural blocking feature recombination, and uses the fuzzy C-means clustering technique to analyze the big data. Through the parallel feature distributed recombination, the cluster center of big data can be optimized according to the index blocking fusion and adaptive optimization methods, traverse the candidate target set of the clustering region, and realize the quantitative evaluation of the green development of the cultural tourism integration industry cluster according to the difference level of the clustering characteristics. The simulation results show that the fusion reliability level of this method is high, and the convergence error is small, which indicates that the reliability of this method is good for the green development of industrial clusters.