INTEGRATED EVALUATION OF LOW-ALTITUDE ECONOMIC DEVELOPMENT USING AN IMPROVED GRA–TOPSIS METHOD
Keywords:
Low-altitude economy, Aerospace industry chain, Comprehensive evaluation, Improved GRA–TOPSIS, Combined weighting, Simulated dataAbstract
The low-altitude economy is emerging as an important growth domain in the transition from pilot exploration to large-scale development. However, existing evaluation frameworks often emphasize industrial scale while insufficiently capturing the joint effects of airspace resources, infrastructure, innovation, application scenarios, market demand, and governance capacity. This study integrates indicators from the aerospace industry chain with low-altitude economic development indicators and develops a multidimensional evaluation system comprising six dimensions and 34 tertiary indicators. A group-decision relative-entropy aggregation procedure is used to derive subjective weights, which are combined with entropy-based objective weights. The resulting weights are incorporated into an improved Grey Relational Analysis–Technique for Order Preference by Similarity to an Ideal Solution (GRA–TOPSIS) framework. Using 12 simulated evaluation units, the method produces a transparent chain from expert scoring and the group decision matrix H to the weighted normalized matrix R, the grey-relational optimal indicator set, Euclidean distances from the positive and negative ideal solutions, and the final relative closeness values. The simulated results distinguish different development levels and illustrate how distance-based and structural similarity information can be integrated. Because the dataset is simulated, the numerical rankings should not be interpreted as empirical regional findings; the study instead provides a reproducible methodological template for subsequent research based on official statistics and enterprise-level data.References
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