基于机器学习的塑料分类回收预测系统  

Plastic Classification and Recycling Prediction System Based on Machine Learning

作　　者：徐向丽[1] 徐颖达 李波[1] XU Xiang-li;XU Ying-da;LI Bo(Ordos Vocational College,Ordos 017010,China;Shanghai Advanced Research Institute,Chinese Academy of Sciences,Shanghai 201210,China)

机构地区：[1]鄂尔多斯职业学院,内蒙古鄂尔多斯017010 [2]中国科学院上海高等研究院,上海201210

出　　处：《塑料科技》2020年第3期82-85,共4页Plastics Science and Technology

基　　金：内蒙古自治区高等学校科学研究项目(NJZY20217)。

摘　　要：塑料分类回收预测系统主要由垃圾接收装置、垃圾预测分类装置、垃圾压缩装置和垃圾回收储存装置4部分组成,其中垃圾预测分类装置凭借提出的塑料预测分类模型执行塑料分类工作。塑料预测分类模型应用深层次的Inception卷积神经网络,提取高度抽象的关键塑料特征。实验结果表明:塑料分类回收预测系统的预测分类准确率高于传统的预测分类模型约2%。The plastic classification and recycling prediction system was mainly composed of four parts: a garbage receiving device, a garbage prediction and classification device, a garbage compression device, and a garbage recovery storage device. The garbage prediction classification device performed the key plastic classification work by virtue of the plastic prediction classification model proposed in this paper. The convolution neural network such as Inception is applied to plastic prediction classification model, so that the key features of high abstraction can be extracted. The experiments show that the accuracy of the prediction classification of the plastic classification and recycling prediction system in this paper is higher than that of the traditional prediction classification model by about 2%.

关 键 词：塑料 机器学习 Inception卷积神经网络 分类回收 

分 类 号：TQ320.1[化学工程—合成树脂塑料工业]