王宝丽，女、副教授，山西省计算机学会理事，中国人工智能学会粒计算与知识发现专业委员会委员，山西省科协科学传播专家，运城市行政审批局信息化评审专家库成员，运城学院大数据技术与应用研究所所长，信科院兼职导师。主持国家级、省部级项目4项，发表学术论文30余篇。

研究方向：粒计算与数据挖掘、智能决策

研究项目：

(1)  国家自然科学基金: 基于粒计算的多属性群分级决策模型与算法研究, 已结题。

(2)  山西省高校科技创新项目：概率语言表达的多粒度群智能决策模型研究, 已结题。

(3)  山西省自然科学基金青年面上项目：复杂大群体决策中的多粒度冲突分析及群体共识策略研究, 在研。

(4)  山西省重点实验室开放课题.：犹豫模糊多粒度智能群决策理论与方法研究，已结题。

代表性论文：

(1) 期刊论文：

[1] Baoli Wang, Jiye Liang. A Novel Preference Measure for Multi-Granularity Probabilistic Linguistic Term Sets and its Applications in Large-Scale Group Decision-Making. International Journal of Fuzzy Systems, 2020, 22(7): 2350–2368. (SCI源刊，中科院3区)

[2]Baoli Wang, Jiye Liang,Jifang Pang. Deviation degree: a perspective on score functions in   hesitant fuzzy sets[J]. International Journal of Fuzzy Systems, 2019, 21(7): 2299-2317. (SCI源刊，中科院3区)

[3] Baoli Wang, Jiye Liang, Yuhua Qian. Preorder Information Based Attributes’ Weights Learning in Multi-attribute Decision Making. Fundamenta Informaticae, 2014, 132(4):331-347.(SCI、EI)

[4] Baoli Wang, Jiye Liang, Yuhua Qian, Chuangyin Dang, A normalized numerical scaling method for the unbalanced multi-granular linguistic sets, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 2015, 23(2):221-243.（SCI、EI、CCF推荐）

[5] Baoli Wang, Jiye Liang, Yuhua Qian. Determining decision makers’ weights in group ranking: a granular computing method. International Journal of Machine Learning and Cybernetics,    2015,6(3):511-521.(SCI、EI)

[6] Chao Zhang, Deyu Li, Jiye Liang, Baoli Wang, MAGDM-oriented dual hesitant fuzzy multigranulation probabilistic models based on MULTIMOORA, International Journal of Machine Learning and Cybernetics, 2021, 12(2):1-23. (SCI源刊，中科院3区)

[7] 王宝丽, 梁吉业, 胡运红. 基于粒计算的犹豫模糊多准则决策方法[J]. 模式识别与人工智能, 2016, 29(3):252-262. (北大核心)

(2) 会议论文：

[1] Baoli Wang, Jiye Liang. A Novel Intelligent Multi-attribute Three-Way Group Sorting Method Based on Dempster-Shafer Theory, RSKT2014, 789-799.（EI）

[2] Baoli Wang, Jiye Liang, Yuhua Qian. Information granularity and granular structure in decisionmaking. In T. Li et al. (Eds.): RSKT 2012, pp. 440–449, 2012.（EI）