Article(id=1319241530372633169, tenantId=1146029695717560320, journalId=1185652524569653253, issueId=1319241501746512444, articleNumber=null, orderNo=null, doi=10.13647/j.cnki.btgkj.2020.01.004, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1566403200000, receivedDateStr=2019-08-22, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1792461291162, onlineDateStr=2026-10-20, pubDate=1582560000000, pubDateStr=2020-02-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1792461291162, onlineIssueDateStr=2026-10-20, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1792461291162, creator=13701087609, updateTime=1792461291162, updator=13701087609, issue=Issue{id=1319241501746512444, tenantId=1146029695717560320, journalId=1185652524569653253, year='2020', volume='46', issue='1', pageStart='1', pageEnd='98', issueExtLink='null', onlineDate='null', pubDate='1582560000000', pubDateStr='2020-02-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1792461284337, creator='13701087609', updateTime=1792735012408, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1320389600552530694, tenantId=1146029695717560320, journalId=1185652524569653253, issueId=1319241501746512444, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1320389600552530695, tenantId=1146029695717560320, journalId=1185652524569653253, issueId=1319241501746512444, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=14, endPage=17, ext={EN=ArticleExt(id=1319241530573959762, articleId=1319241530372633169, tenantId=1146029695717560320, journalId=1185652524569653253, language=EN, title=Prediction of Coke Quality with Multi-layer Neural Network, columnId=1187340472918880861, journalTitle=Science & Technology of Baotou Steel, columnName=Production Practice and Management, runingTitle=null, highlight=null, articleAbstract=

In this paper, it is proposed a method for constructing a prediction model of coke production quality with the neural network technique using the process and production data accumulated during the coke productions of Baotou Steel.

, authors=Jian-wen Lu1, Pei-shan Lu2, Xin Jiang3, Li-jun Fu3, Xiao-zong Jia2, authorsList=Jian-wen Lu, Pei-shan Lu, Xin Jiang, Li-jun Fu, Xiao-zong Jia, authorCompany=null, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1319241530938864211, articleId=1319241530372633169, tenantId=1146029695717560320, journalId=1185652524569653253, language=CN, title=采用多层神经网络预测焦炭质量, columnId=1185882039552193444, journalTitle=包钢科技, columnName=生产实践与管理, runingTitle=null, highlight=null, articleAbstract=

文章提出了一种利用包钢焦炭生产过程中积累的工艺和生产数据,采用神经网络技术,构建焦炭生产质量预测模型的方法。

, authors=芦建文1, 卢培山2, 江鑫3, 付利俊3, 贾晓宗2, authorsList=芦建文, 卢培山, 江鑫, 付利俊, 贾晓宗, authorCompany=null, correspAuthors=null, authorNote=

芦建文(1969-),男,高级工程师,现从事计算机与自动化工作。

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芦建文(1969-),男,高级工程师,现从事计算机与自动化工作。

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芦建文(1969-),男,高级工程师,现从事计算机与自动化工作。

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采用多层神经网络预测焦炭质量
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芦建文 1 , 卢培山 2 , 江鑫 3 , 付利俊 3 , 贾晓宗 2
包钢科技 | 生产实践与管理 2020,46(1): 14-17
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包钢科技 |生产实践与管理 2020 , 46 (1) : 14 -17
采用多层神经网络预测焦炭质量
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address=2.内蒙古包钢钢联股份有限公司煤焦化工分公司,内蒙古 包头 014010, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=[AuthorCompany(id=1319241532746609239, tenantId=1146029695717560320, journalId=1185652524569653253, articleId=1319241530372633169, xref=2., ext=[AuthorCompanyExt(id=1319241532754997848, tenantId=1146029695717560320, journalId=1185652524569653253, articleId=1319241530372633169, companyId=1319241532746609239, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.Coke Chemical Engineering Branch Co. of Inner Mongolia Baotou Steel Union Co., Ltd., Baotou 014010, Inner Mongolia Autonomous Region, China), AuthorCompanyExt(id=1319241532767580761, tenantId=1146029695717560320, journalId=1185652524569653253, articleId=1319241530372633169, companyId=1319241532746609239, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.内蒙古包钢钢联股份有限公司煤焦化工分公司,内蒙古 包头 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芦建文1, 卢培山2, 江鑫3, 付利俊3, 贾晓宗2
作者信息
  • 1.包头钢铁(集团)有限责任公司信息服务中心,内蒙古 包头 014010
  • 2.内蒙古包钢钢联股份有限公司煤焦化工分公司,内蒙古 包头 014010
  • 3.内蒙古包钢钢联股份有限公司技术中心,内蒙古 包头 014010
作者简介:

芦建文(1969-),男,高级工程师,现从事计算机与自动化工作。

Prediction of Coke Quality with Multi-layer Neural Network
Jian-wen Lu1, Pei-shan Lu2, Xin Jiang3, Li-jun Fu3, Xiao-zong Jia2
Affiliations
  • 1.Information Service Center of Baotou Iron & Steel (Group) Co., Ltd., Baotou 014010, Inner Mongolia Autonomous Region, China
  • 2.Coke Chemical Engineering Branch Co. of Inner Mongolia Baotou Steel Union Co., Ltd., Baotou 014010, Inner Mongolia Autonomous Region, China
  • 3.Technical Center of Inner Mongolia Baotou Steel Union Co., Ltd., Baotou 014010, Inner Mongolia Autonomous Region, China
出版时间: 2020-02-25 doi: 10.13647/j.cnki.btgkj.2020.01.004
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文章提出了一种利用包钢焦炭生产过程中积累的工艺和生产数据,采用神经网络技术,构建焦炭生产质量预测模型的方法。

焦炭质量指标  /  焦炭质量模型  /  神经网络

In this paper, it is proposed a method for constructing a prediction model of coke production quality with the neural network technique using the process and production data accumulated during the coke productions of Baotou Steel.

coke quality index  /  coke quality model  /  neural network
芦建文, 卢培山, 江鑫, 付利俊, 贾晓宗. 采用多层神经网络预测焦炭质量. 包钢科技, 2020 , 46 (1) : 14 -17 . DOI: 10.13647/j.cnki.btgkj.2020.01.004
Jian-wen Lu, Pei-shan Lu, Xin Jiang, Li-jun Fu, Xiao-zong Jia. Prediction of Coke Quality with Multi-layer Neural Network[J]. Science & Technology of Baotou Steel, 2020 , 46 (1) : 14 -17 . DOI: 10.13647/j.cnki.btgkj.2020.01.004

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doi: 10.13647/j.cnki.btgkj.2020.01.004
  • 接收时间:2019-08-22
  • 首发时间:2026-10-20
  • 出版时间:2020-02-25
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  • 收稿日期:2019-08-22
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    1.包头钢铁(集团)有限责任公司信息服务中心,内蒙古 包头 014010
    2.内蒙古包钢钢联股份有限公司煤焦化工分公司,内蒙古 包头 014010
    3.内蒙古包钢钢联股份有限公司技术中心,内蒙古 包头 014010
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2种不同金属材料的力学参数
科
Family
属数
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genus
种数
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species
占总种数比例
Percentage of
total species (%)
属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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