Research on the evaluation and pricing of data assets under the circulation value of highway data assets

With the digital transformation of highway construction, a considerable amount of structured, semi-structured, and unstructured data resources have been accumulated, exerting an extremely high application value in the highway sector. The market demand for highway data transactions is gradually escalating, and it becomes particularly crucial to scientifically assess the value of highway data. Nevertheless, at present, the application of highway data has limitations, the value content is indistinct, and a set of methods or models applicable to the valuation of highway data assets has not yet been established. Hence, based on the characteristics of highway data assets, this paper utilizes data mining and machine learning techniques to construct a dynamic valuation model of highway data asset value, which holds reference value for the assessment of highway data value.