基于BP神经网络预测水电站对库表水温及鱼类活动影响——以三峡库区宜昌站为例  

The Predicted Influence of Hydropower Station on Surface Water Temperature and Fish Activity Based on BP Neural Network——Taking Yichang Station in the Three Gorges Reservoir Area as An Example

作　　者：姚田成 谭均军 王慧敏 李勉 YAO Tian-cheng;TAN Jun-jun;WANG Hui-min;LI Mian(Institute of Water Conservancy and Environment,China Three Gorges University,Yichang 443000,Hubei,China)

机构地区：[1]三峡大学水利与环境学院,湖北宜昌443000

出　　处：《水利科技与经济》2021年第1期78-84,共7页Water Conservancy Science and Technology and Economy

摘　　要：大型水利枢纽工程建设不可避免地引起当地流域水温变化,尽可能减少损失成为水利智能化发展的综合考量因素。水温研究为生态保护、经济发展提供可参考的数据方案,对水利发展具有积极意义,但水温的实地测量往往因为诸多因素不可实现。以Matlab为工具,充分利用其强大的矩阵运算功能,结合BP神经网络对水电站库区建成后各因素的综合作用而对水温影响作出预测。通过分析工程建设前后的水温变化,推论其对流域内鱼类活动的影响,为水温数据预测和渔业发展提供一种可行的、较容易操作的思路和方法。The construction of large-scale water conservancy project inevitably causes the change of water temperature in the local river basin,and reducing the loss as far as possible becomes a comprehensive factor for the development of water conservancy intelligence.The study of water temperature provides a reference data scheme for ecological protection and economic development,which is of positive significance to the development of water conservancy.But water temperature field measurements often because of many factors cannot achieve.In this paper,based on the Matlab software,make full use of its powerful matrix operations,combined with BP neural network for hydropower station reservoir area after the completion of a combination of various factors and influence on the temperature forecast,through the analysis of changes in water temperature before and after the project construction,concluded its influence on basin fish activity,for the water temperature data to predict and fishery development provides a feasible train of thought and method is easy to operate.

关 键 词：三峡水电建设 BP神经网络 水温变化 鱼类活动 

分 类 号：TV74[水利工程—水利水电工程]