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.
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