摘要
生物质资源丰富,对生物质进行烘焙预处理后,再利用机器学习(ML)对烘焙生物质进行燃料分级有利于实现生物质能源的规模化应用。本文介绍了机器学习算法在医疗诊断、图像识别、自然语言处理等领域的分类学方面的应用,重点综述了其对烘焙生物质的产物能量及固体产物产量等的预测效果。最后,根据机器学习分类和预测的相互转化,展望了未来将机器学习的分类技术用于烘焙生物质分类的前景。
Biomass resources were abundant.After torrefaction pretreatment,machine learning(ML)was used to classify torrefied biomass as fuel to realize the large-scale application of biomass energy.This paper introduced the application of machine learning algorithms in the fields of medical diagnosis,image recognition and natural language processing,etc.,and focused on the prediction of product energy and solid product yield of torrefied biomass.Finally,according to the mutual transformation of ML classification and prediction,the prospects of applying ML classification techniques to the rorrefied biomass classification in the future was proposed.
作者
刘海云
孙云娟
徐卫
陈义峰
汪东
黄萍
LIU Haiyun;SUN Yunjuan;XU Wei;CHEN Yifeng;WANG Dong;HUANG Ping(Institute of Chemical Industry of Forest Products,CAF/Key Lab.of Biomass Energy and Material,Jiangsu Province/Key Lab.of Chemical Engineering of Forest Products,National Forestry and Grassland Administration/National Engineering Research Center of Low-Carbon Processing and Utilization of Forest Biomass,Nanjing 210042,China;Jiangsu Co-Innovation Center of Efficient Processing and Utilization of Forest Resources,Nanjing Forestry University,Nanjing 210037,China;Sinopec Nanjing Research Institute of Chemical Industry Co.,Ltd.,Nanjing 210048,China)
出处
《林产化学与工业》
CAS
CSCD
北大核心
2024年第6期1-10,共10页
Chemistry and Industry of Forest Products
基金
国家重点研发计划资助项目(2022YFB4202001)
江苏省生物质能源与材料重点实验室基本科研业务费(JSBEM-S-202324)。
关键词
生物质烘焙
机器学习
原料分类
biomass torrefaction
machine learning
raw material classification
