Artificial Intelligence Based Deterioration Model for Development of Bridge Network Maintenance Strategy

基于人工智能的劣化模型用于制定桥梁网络维护策略

• 批准号: LP0883807
• 负责人: Prof Michael Blumenstein
• 金额: $ 29.64万
• 依托单位: Griffith University
• 依托单位国家: 澳大利亚
• 项目类别: Linkage Projects
• 财政年份: 2009
• 资助国家: 澳大利亚
• 起止时间: 2009-12-31 至 2012-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/LP0883807
• 关键词: Artificial; Intelligence; Based; Deterioration; Model

The proposed AI-based methodology in conjunction with a Bridge Management System can tailor-make bridge deterioration models for a given bridge authority. The models so produced will enable effective BMS implementation which generates missing inspection records of past years, establishes optimal MR&R strategies and then reliably forecasts future bridge condition ratings. The methodology will be verified using available bridge datasets of QDMR and GCCC. The methodology is applicable to other bridge authorities throughout Australia and internationally to maintain ageing bridge stock.

所提出的基于人工智能的方法与桥梁管理系统相结合，可以为给定的桥梁当局量身定制桥梁恶化模型。如此生成的模型将能够有效实施 BMS，生成过去几年缺失的检查记录，建立最佳的 MR&R 策略，然后可靠地预测未来的桥梁状况评级。该方法将使用 QDMR 和 GCCC 的可用桥梁数据集进行验证。该方法适用于澳大利亚和国际上的其他桥梁当局，以维护老化的桥梁库存。