Abstract
This paper used the trophic level index (TLI) method combined with the relevant data from 2014 to 2017 to evaluate the water quality of Gaoyou Lake. Meanwhile, based on principal component analysis (PCA) and multiple linear regression (MLR) models on chlorophyll a (Chla), this research developed predictions and an early warning scheme for eutrophication in Gaoyou Lake. The results showed the following: 1. The TLI of Gaoyou Lake showed a significant increasing trend, and the lake was in the state of light to moderate eutrophy. 2. According to the PCA eigenvalues that were greater than 1, principal components (PCs) with a cumulative contribution rate of 76.04% were obtained, and a linear model was further obtained: CChla = 6.146 + 1.209 (Score 1) + 0.583 (Score 2) + 1.095 (Score 3). 3. The credibility of the early warning system reached 75%, which met the requirements of this study. This study provides a scientific basis for the control of eutrophication and improvement of water quality.
Predicting Quality of Life Changes in Hemodialysis Patients Using Machine Learning: Generation of an Early Warning System
