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The schematic diagram of random forest regression structure. 2.2.5. Back Propagation Neural Network (BPNN)
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Background:
Tuberculosis (TB) is a public health problem worldwide, and the influence of meteorological and air pollutants on the incidence of tuberculosis have been attracting interest from researchers. It is of great importance to use machine learning to build a prediction model of tuberculosis incidence influenced by meteorological and air poll...
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Context 1
... Test samples: each new observation variable in the validation set is entered into each decision tree in the random forest for regression output, and the mean output of each decision tree is taken as the final result according to the principle of least mean square deviation. The schematic diagram of the random forest regression structure is shown in Figure 1. The Back propagation neural network, also known as the BP neural network, is one of the most widely used artificial neural networks. ...
Context 2
... support vector regression model (SVR1) that included average daily temperature, precipitation, relative humidity, sunshine hours, PM10, O3, CO and SO2 had the highest root mean square error, mean absolute error and mean absolute percentage error. Figure 10 shows the prediction effect of each model after monthly statistics. After comparison, the prediction trend of BP2 is near the actual incidence, the peak of incidence highly coincides with the actual aggregation time, with high accuracy and minimum error. ...
