基于朴素贝叶斯分类器的垃圾分类系统

Garbage Classification System Based on Naive Bayesian Classifier

选取2008—2018年上海市生活垃圾数据,首先利用灰色预测模型对未来4年垃圾产生量进行预测得出:未来垃圾产生量将会继续增长,给出垃圾分类的必要性;然后设计朴素贝叶斯分类器,使用已有数据进行训练,建立生活垃圾分类系统并给出分类判断标准;最后,结合垃圾分类系统给出相应的政策建议,以便更准确高效地进行垃圾分类处理。

This paper selects 2008—2018 Shanghai municipal solid waste data,first uses the gray prediction model to predict the garbage production in the next four years,the future garbage production will continue to grow,which obtains the necessity of garbage classification;then designs the naive Bayes classifier,uses the existing data for training,establishes the garbage classification system and gives the classification criteria;finally,combined with the garbage classification system,the corresponding policy recommendations are given in order to more accurately and efficiently carry out garbage classification.