Cross-modal data processing method for cultural enabling airport design evaluation

Through the adaptive time alignment algorithm and convolutional neural network model to process multi-source data, the detection and repair of time aberration and low-quality data points are solved, and high-quality multi-source evaluation data processing and scientific evaluation of culturally empowered airport design are realized.

CN120216892APending Publication Date: 2025-06-27NANJING TECH UNIV +1
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Patent Information

Application Number
CN202510293619.4
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-03-13
Publication Date
2025-06-27

AI Technical Summary

Technical Problem

The prior art faces the difficulties of time aberration and automatic detection and repair of low-quality data points when processing multi-source data, which affects the accuracy and reliability of data analysis.

Method used

Adaptive time alignment algorithm is used to timely align multi-source data, and the convolutional neural network model is used to automatically detect and repair low-quality or noisy data points, build a multi-dimensional semantic space to obtain consistent multi-source evaluation data, and finally evaluate the cultural elements of cultural empowered airport design through a comprehensive scoring mechanism.

Benefits of technology

It significantly improves the accuracy and reliability of data processing, provides scientific, comprehensive and efficient evaluation tools for culturally empowering airport design, ensuring high quality and credibility of evaluation results.

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Abstract

The invention discloses a cross-modal data processing method for cultural enabling airport design evaluation, and relates to the technical field of cross-modal data analysis and processing, and the method comprises the steps: obtaining time alignment multi-source evaluation data through an adaptive time alignment algorithm based on preprocessed multi-source evaluation data; based on a convolutional neural network model, constructing a multi-source quality enhancement model, and inputting the time alignment multi-source evaluation data into the multi-source quality enhancement model to obtain high-quality multi-source evaluation data; based on the high-quality multi-source evaluation data, constructing a multi-dimensional semantic space, and obtaining position information and association rules in the multi-dimensional semantic space; obtaining consistency multi-source evaluation data by analyzing the position information and the association rule; and based on the consistent multi-source evaluation data, through a comprehensive scoring mechanism, evaluating culture elements of the culture enabling airport. According to the invention, through the adaptive time alignment algorithm and the convolutional neural network model, the accuracy and reliability of data processing are significantly improved.
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