基于机器算法预测模型的水库叠梁门措施对水库下泄水温调节作用的验证研究  

Verification Study on the Effect of Reservoir Stoplog Measures on Reservoir Discharge Water Temperature Regulation Based on Machine Algorithm Prediction Model

作　　者：朴虹奕 周湘山 徐劲草 张磊 秦甦 PIAO Hongyi;ZHOU Xiangshan;XU Jingcao;ZHAN Lei;QIN Su(PowerChina Chengdu Engineering Corporation Limited,Chengdu Sichuan 611130)

机构地区：[1]中国电建集团成都勘测设计研究院有限公司,四川成都611130

出　　处：《四川水力发电》2024年第6期116-119,133,共5页Sichuan Hydropower

摘　　要：通过使用R语言编程软件对原始数据的归一化处理和参数的筛选与成分相关性分析,建立了基于机器学习5种算法预测模型。结果表明:通过对模型的训练和修正,5种基于机器学习的水库下泄水温预测模型中,支持向量机模型的效果最佳,模型预测值的准确度可以达到0.78。支持向量机水库水温预测模型可以实现对水温的监测和控制,从而对水库的生态环境影响及时采取优化措施,并进行结果的预测验证。By using R language programming software to first normalize the original data,screen parameters and screen component correlation,five prediction models based on machine learning algorithms have been established.The results show that through the training and modification of the model,the support vector machine model has the best effect among the 5 kinds of machine learning-based prediction models of reservoir drainage water temperature,and the accuracy of this model prediction value has reached to 0.78.Support vector machine reservoir water temperature prediction model can not only realize the monitoring and control of water temperature,but also to take timely optimization measures and to get immediate validation for the ecological environment of the reservoir,and verify the prediction results.

关 键 词：机器学习 统计预测模型 水温 鱼类繁殖 

分 类 号：P332.6[天文地球—水文科学]