A model and a method for predicting the occurrence of heat stroke based on machine learning
A machine learning and random forest model technology, which is applied to models and fields for predicting the occurrence of heat stroke based on machine learning, can solve the problems of poor reliability of the prediction model and lack of corresponding evaluation, and achieve the improvement effect, reduce economic losses, and fit the prediction effect well. Effect
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[0039] The technical solutions of the present invention will be further described below in conjunction with the accompanying drawings and examples of implementation.
[0040] A model and method for predicting the occurrence of heat stroke based on machine learning, the specific process is as follows figure 1 shown, including the following steps:
[0041] Step 1: Establish a database of high temperature events in typical high temperature cities in my country over the years
[0042] Organize the economic and sociological indicators and meteorological data of typical cities in China, including short-term lag data of meteorological factors such as city, date, number of heat strokes on the day, average temperature from the previous day to five days, maximum temperature, and relative humidity, and their corresponding The average value of long-term meteorological data such as the previous 5 years; it also includes socioeconomic variables such as gross national product, population, u...
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