NNRF:神经网络河流预报
神经网络河流预报(Neural Network River Forecasting,常缩写为NNRF)是一种融合人工智能技术的现代水文预测方法。该术语常见于多学科交叉领域,涵盖水文学、计算机科学和环境工程等,旨在利用神经网络模型对河流流量、水位变化等进行高精度预测,以支持水资源管理与防灾决策。缩写形式NNRF便于在学术文献和实际应用中快速书写和传播。
Neural Network River Forecasting具体释义
Neural Network River Forecasting的英文发音
例句
- Study of RBF Neural Network River Water Turbidity Forecasting Based on Phase Space Reconstruction
- 基于相空间重构的RBF江水浊度预报研究
- In order to diminish the system error, this study tried to introduce the weather radar rainfall technique and BP neural network technique into River Basin flood forecasting, and a flood forecasting model was developed based on the distributed hydrological model.
- 为了减小系统误差,本次研究尝试将雷达测雨技术、BP神经网络技术引入流域洪水预报中,并建立基于分布式水文模型的洪水预报模型。
- The artificial neural network ( ANN ) method is studied for use in river channel flood forecasting, the result show that the method can be applied in practice.
- 论文探索了人工神经网络方法(ANN)在河道洪水预报中的应用;该结果具有一定实用前景。
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