Abstract
Many studies have attempted to predict chlorophyll-a concentrations using multiple regression models and validating them with a hold-out technique. In this study commonly used machine learning models, such as Support Vector Regression, Bagging, Random Forest, Extreme Gradient Boosting (XGBoost), Recurrent Neural Network (RNN), and Long–Short-Term Memory (LSTM), are used to build a new model to predict chlorophyll-a concentrations in the Nakdong River, Korea. We employed 1–step ahead recursive prediction to reflect the characteristics of the time series data. In order to increase the prediction accuracy, the model construction was based on forward variable selection. The fitted models were validated by means of cumulative learning and rolling window learning, as opposed to the hold–out technique. The best results were obtained when the chlorophyll-a concentration was predicted by combining the RNN model with the rolling window learning method. The results suggest that the selection of explanatory variables and 1–step ahead recursive prediction in the machine learning model are important processes for improving its prediction performance.
Highlights
Climate change has brought about numerous problems, including heat waves, droughts, increased pollution, and algal blooms
Cumulative learning and rolling window learning were used for the predictions
The results show that Recurrent Neural Network (RNN) outperformed the remaining machine learning models
Summary
Climate change has brought about numerous problems, including heat waves, droughts, increased pollution, and algal blooms. Since rivers and lakes are utilized as water sources, it is necessary to manage freshwater algae appropriately in order to ensure clean and safe water supplies [1]. The use of tap water is restricted when large quantities of algae are found in water reservoirs, as several water purification issues can arise, such as clogged paper filters and bad odor caused by substances such as geosmin and 2-Methylisoborneol (MIB). By predicting algal blooms in advance and responding swiftly to curtail algae growth, it is possible to minimize the damage and ensure uninterrupted purified water production. Freshwater algae are typically minute floating microalgae with photosynthetic pigments called chlorophyll. Chlorophyll-a is a pigment that absorbs the light needed for plants to photosynthesize
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