| 基于多粒度概率粗糙集与MULTIMOORA的q-RO模糊多属性群决策 |
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| 引用本文： | 白文慧,张超,陈炜哲,李德玉,上官学奎,马瑾男.基于多粒度概率粗糙集与MULTIMOORA的q-RO模糊多属性群决策[J].重庆邮电大学学报(自然科学版),2021,33(5):769-779. |
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| 作者姓名： | 白文慧 张超 陈炜哲 李德玉 上官学奎 马瑾男 |
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| 作者单位： | 山西大学 计算机与信息技术学院,太原030006;山西大学 计算机与信息技术学院,太原030006;计算智能与中文信息处理教育部重点实验室(山西大学),太原030006;山西省信息产业技术研究院有限公司,太原030012 |
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| 基金项目： | 国家自然科学基金（61806116，62072294，61972238）；山西省重点研发计划（国际科技合作）项目（201903D421041，201803D421004）；2020年小店区-山西大学产学研合作项目；山西省高等学校青年科研人员培育计划；山西省高等学校优秀成果培育项目（2019SK036）；山西省自然科学基金（201801D221175，201901D211176，201901D211414） |
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| 摘 要： | 为了探索q-RO(q-rung orthopair)模糊信息系统中具备稳定决策结果的多属性群决策方法,依据多粒度概率粗糙集与MULTIMOORA(multi-objective optimization by ratio analysis plus the full MULTIplicative form)建立了一种新的q-RO模糊多粒度计算模型,并用于求解多属性群决策问题.结合q-RO模糊概率粗糙集与多粒度粗糙集,提出了多粒度q-RO模糊概率粗糙集模型.利用离差最大化法计算属性权重与决策者权重,进一步建立了基于多粒度概率粗糙集与MULTIMOORA的q-RO模糊多属性群决策方法,该方法考虑了决策风险与容错能力,可提供稳定的决策结果.通过2个实际算例验证了所建立方法的可行性与有效性.
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| 关 键 词： | 多粒度 概率粗糙集 q-RO模糊信息系统 多属性群决策 MULTIMOORA |
| 收稿时间： | 2021/5/19 0:00:00 |
| 修稿时间： | 2021/6/21 0:00:00 |
q-RO fuzzy multi-attribute group decision making based on multigranulation probabilistic rough sets and MULTIMOORA |
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| BAI Wenhui,ZHANG Chao,CHEN Weizhe,LI Deyu,SHANGGUAN Xuekui,MA Jinnan.q-RO fuzzy multi-attribute group decision making based on multigranulation probabilistic rough sets and MULTIMOORA[J].Journal of Chongqing University of Posts and Telecommunications,2021,33(5):769-779. |
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| Authors: | BAI Wenhui ZHANG Chao CHEN Weizhe LI Deyu SHANGGUAN Xuekui MA Jinnan |
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| Institution: | School of Computer and Information Technology, Shanxi University, Taiyuan 030006, P. R. China;School of Computer and Information Technology, Shanxi University, Taiyuan 030006, P. R. China;Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education(Shanxi University), Taiyuan 030006, P. R. China;Shanxi Information Industry Technology Research Institute Co. Ltd., Taiyuan 030012, P. R. China |
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| Abstract: | In order to explore stable multi-attribute group decision-making results in q-RO (q-rung orthopair) fuzzy information systems, a new q-RO fuzzy multi-granularity computing model is constructed in light of multigranulation probabilistic rough sets and MULTIMOORA (multi-objective optimization by ratio analysis plus the full multiplicative form) for solving multi-attribute group decision making problems. First, multigranulation q-RO fuzzy probabilistic rough set models are put forward by combining q-RO fuzzy probabilistic rough sets with multigranulation rough sets. Then, the maximum deviation method is utilized to calculate attribute weights and expert weights, and a q-RO fuzzy multiple-attribute group decision making method is further constructed based on multigranulation probabilistic rough sets and MULTIMOORA, which can provide stable decision making results via considering decision risks and fault-tolerance capabilities. Finally, the validity and the effectiveness of the established method are verified by two realistic case studies. |
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| Keywords: | multi-granularity probabilistic rough sets q-RO fuzzy information systems multi-attribute group decision making multi-objective optimization by ratio analysis plus the full MULTIplicative form (MULTIMOORA) |
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