A sample generation method and device for a railway station building
By acquiring and processing characteristic parameters of railway station building lifecycle stages, and constructing sample data to train machine learning models, the problem of low accuracy in predicting carbon emissions from railway station buildings in existing technologies is solved, and more accurate carbon emission prediction and management are achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- CHINA RAILWAY CONSTR GROUP CO LTD
- Filing Date
- 2026-04-09
- Publication Date
- 2026-07-17
AI Technical Summary
Existing carbon emission prediction methods in railway stations suffer from low prediction accuracy and lack of real-time performance, failing to meet the needs of modern carbon emission management, especially when faced with complex and multivariate influencing factors.
By acquiring characteristic parameters of historical railway station buildings at each stage of their life cycle, standardizing them, constructing covariance and load matrices, determining contribution degree, contribution rate, and contribution weight, and selecting key features to construct sample data for targeted training of machine learning models.
This improves the accuracy and relevance of model training, enabling more precise prediction of carbon emissions from railway stations at different lifecycle stages, and supporting real-time carbon emission management and optimization.
Smart Images
Figure CN122412947A_ABST