Article(id=1321895070236783616, tenantId=1146029695717560320, journalId=1225396423026438145, issueId=1321894989857141221, articleNumber=null, orderNo=null, doi=null, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1760976000000, receivedDateStr=2025-10-21, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1793093944367, onlineDateStr=2026-10-27, pubDate=1787587200000, pubDateStr=2026-08-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793093944367, onlineIssueDateStr=2026-10-27, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793093944367, creator=13701087609, updateTime=1793093944367, updator=13701087609, issue=Issue{id=1321894989857141221, tenantId=1146029695717560320, journalId=1225396423026438145, year='2026', volume='46', issue='8', pageStart='1', pageEnd='324', issueExtLink='null', onlineDate='null', pubDate='1787587200000', pubDateStr='2026-08-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1793093925203, creator='13701087609', updateTime=1793094606751, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1321897848535372687, tenantId=1146029695717560320, journalId=1225396423026438145, issueId=1321894989857141221, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1321897848535372688, tenantId=1146029695717560320, journalId=1225396423026438145, issueId=1321894989857141221, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=266, endPage=277, ext={EN=ArticleExt(id=1321895070459080704, articleId=1321895070236783616, tenantId=1146029695717560320, journalId=1225396423026438145, language=EN, title=Design and Implementation of an Intelligent Evaluation System for Closed/Abandoned Mine Resources Based on Adaptive Analytic Hierarchy Process, columnId=null, journalTitle=Mining Research and Development, columnName=null, runingTitle=null, highlight=null, articleAbstract=
To solve the problems of strong subjectivity, poor dynamic adaptability, and low evaluation efficiency in the resource development of closed/abandoned mines, a multi-dimensional evaluation index system with a three-tier framework of "target layer, criterion layer, and index layer" was constructed under the guidance of the collaborative concept of "energy-oriented, resource-oriented, and function-oriented" utilization. By integrating algorithms such as Analytic Hierarchy Process (AHP), Light Gradient Boosting Machine (LightGBM), and Isolation Forest, an intelligent model for dynamic weight optimization and consistency check was constructed. The intelligent evaluation system for closed/abandoned mine resources based on adaptive AHP was developed using Java language, with the Vue. js and Spring Boot frameworks, and technologies including MySQL, Redis, Apache POI, and Docker. In the system, functions such as data import, hierarchical analysis calculation, and result visualization are realized, and the shortcomings of traditional evaluation methods, such as static weights and excessive manual intervention, are overcome. A case study was conducted under the actual conditions of the Longdong Coal Mine. The results show that the system can accurately reflect the characteristics of the mine resources and exhibits good practicality. The research results can provide a replicable technical path for the intelligent evaluation of closed/abandoned mine resources.
, authors=Dandan Li
1, 2, Qinjie Liu
1, 2, Youxing Yang
1, 2, Tian Lan
1, 2, Jiaju Zhang
1, 2, Qiang Chen
1, 2, authorsList=Dandan Li, Qinjie Liu, Youxing Yang, Tian Lan, Jiaju Zhang, Qiang Chen, authorCompany=null, correspAuthors=Qinjie Liu, 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=1321895071025311746, articleId=1321895070236783616, tenantId=1146029695717560320, journalId=1225396423026438145, language=CN, title=基于自适应层次分析法的关退矿井资源智能评价系统设计与实现, columnId=1226462295946085268, journalTitle=矿业研究与开发, columnName=矿山机电与矿业智能化, runingTitle=null, highlight=null, articleAbstract=
为解决关退矿井资源开发中评估方法主观性强、动态适应性差、评估效率低等问题,以“能源化、资源化、功能化”三化协同理念为指导,构建了“目标层-准则层-指标层”三层架构的多维度评价指标体系。综合利用层次分析法(AHP)、轻量梯度提升机(LightGBM)、孤立森林(iForest)等算法,构建了权重动态优化与一致性检验的智能化模型,并采用Java语言,基于Vue.js与Spring Boot框架,利用MySQL、Redis、Apache POI及Docker等技术,开发了自适应层次分析法的关退矿井资源智能评价系统,实现了数据导入、层次分析计算与结果可视化等功能,克服了传统评估方法中权重静态与人工干预过多的不足。针对龙东煤矿的实际条件进行案例分析,结果表明该系统能够准确反映矿井资源特征,并具有良好的实用性。研究结果可为关退矿井资源智能评价提供可复制的技术路径。
, authors=李丹丹
1, 2, 刘钦节
1, 2, 杨友兴
1, 2, 蓝天
1, 2, 张家驹
1, 2, 陈强
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