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基于BP神经网络的在建水利工程度汛安全评价模型OA

Flood safety evaluation model for under-construction water conservancy projects based on BP neural network

中文摘要英文摘要

为提升在建水利工程度汛安全评价的智能化水平,构建了一种基于反向传播(Back Propagation,BP)神经网络的在建水利工程度汛安全状况智能评价模型.该模型考虑多维度指标体系,利用BP神经网络针对非线性问题的学习能力,通过实际工程案例数据的训练,对在建水利工程的度汛安全水平进行预测和分析.研究结果表明,该模型预测结果最大相对误差在4%以内,表现出良好的泛化能力,可有效辅助水行政主管部门和工程参建单位快速开展度汛安全评价.研究可为在建水利工程度汛安全智慧化管理提供参考.

To enhance the intelligence level of flood safety evaluation for water conservancy projects under construction,an intelligent evaluation model for flood safety status of water conservancy projects under construction based on Back Propagation(BP)neural network was constructed.This model considers a multidimensional indicator system and utilizes the learning ability of BP neural network for nonlinear problems.Through training with actual engineering case data,it predicts and analyzes the flood safety level of water conservancy projects under construction.The research results indicate that the maximum relative error of the model's prediction results is within 4%,demonstrating good generalization ability and effectively assisting water administrative authorities and engineering participating units in quickly conducting flood safety evaluations.This study can provide reference for the intelligent management of flood safety in water conservancy projects under construction.

郭秀琴;储善鹏;陈素明;王浩然

浙江省水利防汛技术中心,杭州 310016浙江省水利防汛技术中心,杭州 310016浙江省水利防汛技术中心,杭州 310016浙江省水利防汛技术中心,杭州 310016

建筑与水利

在建水利工程度汛安全BP神经网络评价模型样本预测

under-construction water conservancy projectsflood safetyBP neural networkevaluation modelsample prediction

《中国防汛抗旱》 2026 (4)

35-40,6

10.16867/j.issn.1673-9264.2025407

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