Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Structural depth prediction method based on full-scale asphalt pavement full-life-cycle test and feedback neural network
The invention relates to a construction depth prediction method based on a full-scale asphalt pavement life cycle test and a feedback neural network, and belongs to the technical field of roads. The asphalt pavement structure depth prediction method based on the full-scale pavement full-life cycle test and the feedback neural network algorithm is completely the same as a to-be-predicted road in structure, material, load action mode, natural environment and other conditions, and can obtain anti-skid performance long-term evolution data capable of completely covering the full-life cycle of the asphalt pavement; anti-skid performance prediction is carried out on the basis, the precision and reliability of performance prediction can be greatly improved, and therefore the precision and reliability of pavement design are guaranteed. The prediction method is used for predicting the anti-skid performance of the asphalt pavement in the whole life cycle, and necessary reference and basis are provided for structural design and maintenance decision making of the asphalt pavement.
本发明涉及了一种基于足尺沥青路面全寿命周期试验及反馈神经网络的构造深度预测方法，属于公路技术领域。本发明基于足尺路面全寿命周期试验及反馈神经网络算法的沥青面层构造深度预测方法，与拟预测道路的结构、材料、荷载作用方式、自然环境等条件完全相同，能够获得可完整覆盖沥青路面全寿命周期的抗滑性能长期演化数据，在这个基础上开展的抗滑性能预测，能够大大提高性能预测的精度和可靠性，从而保证路面设计的精准与可信度。本发明的预测方法，用于预测沥青路面在全寿命周期内的抗滑性能，为沥青路面结构设计和养护维修决策提供必要的参考和依据。
Structural depth prediction method based on full-scale asphalt pavement full-life-cycle test and feedback neural network
The invention relates to a construction depth prediction method based on a full-scale asphalt pavement life cycle test and a feedback neural network, and belongs to the technical field of roads. The asphalt pavement structure depth prediction method based on the full-scale pavement full-life cycle test and the feedback neural network algorithm is completely the same as a to-be-predicted road in structure, material, load action mode, natural environment and other conditions, and can obtain anti-skid performance long-term evolution data capable of completely covering the full-life cycle of the asphalt pavement; anti-skid performance prediction is carried out on the basis, the precision and reliability of performance prediction can be greatly improved, and therefore the precision and reliability of pavement design are guaranteed. The prediction method is used for predicting the anti-skid performance of the asphalt pavement in the whole life cycle, and necessary reference and basis are provided for structural design and maintenance decision making of the asphalt pavement.
本发明涉及了一种基于足尺沥青路面全寿命周期试验及反馈神经网络的构造深度预测方法，属于公路技术领域。本发明基于足尺路面全寿命周期试验及反馈神经网络算法的沥青面层构造深度预测方法，与拟预测道路的结构、材料、荷载作用方式、自然环境等条件完全相同，能够获得可完整覆盖沥青路面全寿命周期的抗滑性能长期演化数据，在这个基础上开展的抗滑性能预测，能够大大提高性能预测的精度和可靠性，从而保证路面设计的精准与可信度。本发明的预测方法，用于预测沥青路面在全寿命周期内的抗滑性能，为沥青路面结构设计和养护维修决策提供必要的参考和依据。
Structural depth prediction method based on full-scale asphalt pavement full-life-cycle test and feedback neural network
基于足尺沥青路面全寿命周期试验及反馈神经网络的构造深度预测方法
ZHOU XINGYE (Autor:in) / WANG XUDONG (Autor:in) / GUAN WEI (Autor:in) / WU JIANGFENG (Autor:in) / WAN CHENGUANG (Autor:in) / LIAO JIANGLIN (Autor:in) / HUANG GUANGXI (Autor:in)
27.10.2023
Patent
Elektronische Ressource
Chinesisch
IPC:
G06F
ELECTRIC DIGITAL DATA PROCESSING
,
Elektrische digitale Datenverarbeitung
/
E01C
Bau von Straßen, Sportplätzen oder dgl., Decken dafür
,
CONSTRUCTION OF, OR SURFACES FOR, ROADS, SPORTS GROUNDS, OR THE LIKE
/
G06N
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
,
Rechnersysteme, basierend auf spezifischen Rechenmodellen
| Europäisches Patentamt | 2023
Structural depth prediction method based on full-scale asphalt pavement full-life-cycle test
| Europäisches Patentamt | 2023
Track depth prediction method based on full-scale asphalt pavement full-life-cycle test
| Europäisches Patentamt | 2023
| Europäisches Patentamt | 2023
| Europäisches Patentamt | 2023