Research on Water Quality Prediction System for Shrimp Farming Based on Spectral Technology
郑祉盈 1俞国庆1
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作者信息
1. 广东白云学院,广东 广州 510000
折叠
摘要
随着水产养殖业的快速发展,对虾养殖水质的实时监测与预测显得尤为重要.本研究提出一种基于光谱技术的对虾养殖水质实时预测系统,通过高光谱成像仪获取水质原始光谱数据,结合卷积平滑滤波(Savitzky-Golay Smoothing,SGS)和连续投影算法(Successive projections algorithm,SPA)进行数据处理,并采用最小二乘支持向量机(Least Squares Support Vector Machine,LS-SVM)对对虾养殖水质进行预测.预测模型的决定系数(R2)和均方根误差(RMSE)分别为0.85 mg/L和14.82 mg/L,表明其在对虾养殖水质预测中具备优越的性能.
Abstract
With the rapid development of aquaculture,real-time monitoring and prediction of water quality in shrimp farming has become particularly important.This study proposes a real-time prediction system for shrimp aquaculture water quality based on spectral technology.The raw spectral data of water quality is obtained through a hyperspectral imager,and the data is processed using Convolutional Smoothing(SGS)and Continuous Projections Algorithm(SPA).The Least Squares Support Vector Machine(LS-SVM)is used to predict the water quality of shrimp aquaculture.The determination coefficient(R2)and root mean square error(RMSE)of the prediction model are 0.85 and 14.82mg/L,respectively,indicating its superior performance in predicting water quality in shrimp farming.
关键词
光谱技术/对虾养殖/水质预测/预测模型
Key words
spectral technology/shrimp farming/water quality prediction/predictive model
维普
万方数据