Abstract: According to the characteristics of small samples and sudden change of some According to the characteristics of small samples and sudden change of some sections in Three Gorges, the ELS-SVM water quality prediction model for Three Gorges was proposed, which consisted of Equal Level Pretreatment Model (ELPM) and Least Squares Support Vector Machines (LS-SVM). ELPM was brought forward to preprocess raw time series data to enhance the smoothness, and Simulated Annealing (SA) algorithm was used for choosing the optimal parameters of LS-SVM. The experimental results indicate that, compared to the typical forecasting models in limited samples prediction, the ELS-SVM forecasting model is superior to the others in water quality parameter prediction of Three Gorges.

Key words: pretreatment, Least Squares Support Vector Machine (LS-SVM), Simulated Annealing (SA), Three Gorges, water quality prediction

摘要： 根据三峡库区某些断面水质监测数据具有样本小、成库前后数据出现跳变的特点，提出一种适用于三峡库区的水质参数预测模型（ELS-SVM）。ELS-SVM通过建立数据预处理模型对原始小样本时序数据进行处理，增强了时序数据的平稳性，并使用模拟退火（SA）算法优选最小二乘支持向量机（LS-SVM）模型参数。与典型的小样本预测模型的比较实验表明，ELS-SVM模型更适用于三峡库区小样本水质时序数据的预测。

关键词: 预处理, 最小二乘支持向量机, 模拟退火, 三峡库区, 水质参数预测