提出一种基于多因素权重分析的分类模型（K-means-EWM-BP）来预测农村居民的清洁取暖接受度。首先,基于实地调研数据,选取农村居民家庭年总收入、性别、年龄、受教育程度作为聚类特征对农村居民分类;其次,在分类的基础上,对各类别农村居民的清洁取暖接受度影响因素进行多因素权重分析;最后,构建K-means-EWM-BP模型,实现对农村居民清洁取暖接受度的预测及验证。结果表明：1）受访农村居民可分为3类,其中清洁取暖接受度主要受教育程度影响的农村居民（类别1）占比31%,清洁取暖接受度主要受家庭年总收入影响的农村居民（类别2）占比43%,清洁取暖接受度主要受性别影响的农村居民（类别3）占比26%。2）类别1农村居民清洁取暖接受率预测值为95%,类别2农村居民清洁取暖接受率预测值为100%,类别3农村居民清洁取暖接受率预测值为72%。3）与EWM-BP模型和BP模型相比,K-means-EWM-BP模型预测准确性达到91.43%,高于准确性为87.14%的EWM-BP模型和准确性为80%的BP模型,同时标准误差（RMSE）与EWM-BP模型和BP模型相比分别降低0.01和0.06。
Abstract
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.
关键词
可再生能源 /
农村地区 /
预测 /
多因素权重分析 /
清洁取暖
Key words
renewable energy /
rural areas /
forecasting /
multi-factor weight analysis /
clean heating
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基金
国家自然科学基金（72274148; 52008328）; 陕西省创新能力支撑计划-青年科技新星项目（2023KJXX-043）; 陕西省科协青年人才托举计划（20220425）
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