RESEARCH ON CLASSIFICATION AND PREDICTION METHOD OF RURAL RESIDENTS’ACCEPTANCE FOR CLEAN HEATING BASED ON MULTI-FACTOR WEIGHT ANALYSIS

In this study，a classification model based on multi-factor weight analysis（K-means-EWM-BP）is proposed to forecast the acceptability of clean heating for rural residents. Firstly，rural residents are classified based on data from a field survey by taking gender，age，education level，and total annual household income as clustering characteristics. Secondly，on the basis of classification，multi-factor weight analysis is carried out on the influence factors of the acceptability of clean heating of various rural residents. Finally，the K-mean-EWM-BP model is constructed to forecast and verify the acceptability of clean heating for rural residents.The results show that：1）the rural residents can be divided into three categories，with 31% influenced by education level （category 1），43% by annual household income（category 2），and 26% by gender（category 3）. 2）The forecasted acceptance rate of clean heating for rural residents in category 1 is 95%，the forecasted acceptance rate of clean heating for rural residents in category 2 is 100%，and the forecasted acceptance rate of clean heating for rural residents in category 3 is 72%. 3）The K-means-EWM-BP model achieves an accuracy of 91.43% in forecasting the acceptance rate of clean heating by farmers，surpassing both the EWM-BP model（with an accuracy of 87.14%）and the BP model（with an accuracy of 80%）. Meanwhile，the root mean square error of the K-means-EWM-BP model declines by 0.01 and 0.06 relative to the EWM-BP model and the BP model，respectively. © 2024 Science Press. All rights reserved.