A construction design scheme optimization method, device and equipment and a storage medium
By combining multi-task deep learning models and convolutional kernel tools, the design scheme for foundation pit engineering is optimized, solving the problem of failure to dynamically adapt in traditional design modes. This achieves a balance between safety and economy during construction, and improves the design rationality and construction adaptability of foundation pit engineering.
CN122154026APending Publication Date: 2026-06-05HUNAN CITY UNIV
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- HUNAN CITY UNIV
- Filing Date
- 2026-02-13
- Publication Date
- 2026-06-05
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Figure CN122154026A_ABST
Abstract
The present application relates to the technical field of construction management, and more particularly to a construction design scheme optimization method, device, equipment and storage medium; standardized construction data is predicted according to a multi-task deep learning model to obtain a foundation pit excavation predicted deformation degree; the standardized construction data is evaluated according to a preset convolution kernel, a preset time axis and a preset response parameter value to obtain a foundation pit excavation evaluation deformation degree; a construction design scheme is obtained, and the construction design scheme is optimized according to the foundation pit excavation evaluation deformation degree and the foundation pit excavation predicted deformation degree to obtain a standard design scheme; the multi-task deep learning model and the convolution kernel are used to mine features, the construction design scheme is optimized, engineering safety and economy are balanced, fine management and control of the foundation pit are assisted, and the quality and comprehensive benefits of project construction are improved.
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