2022 GSUA大会

时间：2022年11月12-13日

地点：腾讯会议：637-5534-3263、bat365中文官方网站A0305

1）报告题目：Reverse Grey Relational Analysis Models

报告人：刘思峰（南京航空航天大学）

报告时间：11月12日 9:05-9:35

报告摘要：

The definition of reverse sequence has been given at first based on analysis of relative position and change trend of sequences. Then, several different negative grey relational analysis models, such as the negative grey similarity relational analysis model, the negative grey absolute relational analysis model, the negative grey relative relational analysis model, the negative grey comprehensive relational analysis model, and the negative Deng's grey relational analysis model have been put forward based on the corresponding common grey relational analysis models.

报告人简介：

主要从事“灰色系统理论”和“复杂装备研制管理”等领域的教学和研究工作。主持国家重大、重点课题和国际合作项目多项；发表论文800多篇,其中SCI, SSCI收录论文185篇（JCR一区论文92篇）;出版著作32种，在美、英、德、罗、新等国出版不同语种的外文著作12种；文献被国内外学者引用4.18万次。入选斯坦福大学研究组发布的全球Top 2%科学家榜单和百度学术系统科学领域百名高被引作者榜第一名， H-指数 91。以第一完成人获省部级科技成果奖21项，其中一等奖7项，二等奖12项；2018年获国家级教学成果二等奖。主持完成国家一流课程、国家精品课程、国家精品资源共享课程、国家精品在线开放课程、国家精品教材和“十一五”“十二五”国家规划教材16项。

2）报告题目：智慧交通大数据下的灰色预测与决策研究

报告人：肖新平（武汉理工大学）

报告时间：11月12日 9:35-10:05

报告摘要：

智慧交通大数据可用于公共交通服务、交通引导、物流调度优化。要发挥大数据所蕴含的资源优势，需要从数据中提取隐含的、有用的信息。本报告将介绍智慧交通大数据下的灰色预测与决策方法与应用。

报告人简介：

武汉理工大学二级教授、博士生导师，主要研究方向为灰色系统理论、统计预测与决策、应用数学与力学等，担任国际灰色系统与不确定分析学会副会长、中国优选法统筹法与经济数学研究会理事及灰色系统专业委员会副理事长、中国工程概率统计学会常务理事、中国运筹学会不确定系统分会常务理事、湖北省运筹学会副理事长等。主持国家自然科学基金面上项目4项、教育部博士点专项科研基金2项、以及教育部留学回国人员科研启动基金、交通部科技人才专项经费、湖北省教育厅科研项目、武汉市重大软科学项目等20余项；出版专著3部，发表学术期刊论文100余篇，其中SCI/EI收录60余篇。

3）报告题目：任意Ɩ(Ɩ≤n）阶差分定比关联度及其性质”（On Incidence Degree With Fixed-ratio Ɩ-Order-Difference For Any Ɩ(Ɩ≤n）And Its Properties）

报告人：魏勇（西华师范大学）

报告时间：11月12日 10：30-11:00

报告摘要：

本文给出了任意 Ɩ(Ɩ≤n）阶差分定比关联度的定义，分别从差分序列角度和原始序列角度讨论了它们各自的完全相关、接近完全相关的实质，即完全相关的代数意义，接近完全相关的拓扑意义，以及它们的几何意义，提炼了任意 Ɩ(Ɩ≤n）阶差分定比关联度各类的关联类公理。

报告人简介：

博士,1992年在法国奥尔良大学获得应用数学深入研究阶段文凭（D.E.A文凭）,1997年在西南石油大学获得工学博士学位。现任西华师范大学教授，中国优选法统筹法与经济数学研究会灰色系统专业委员会副理事长，Grey Systems Theory and Application（英国）、International Journal of Uncertainty and Innovation Research（中国台湾）编委，Mathematical Reviews（美国）评论员。在国际期刊、中文核心期刊发表论文100余篇，被 SCI、EI 收录50余篇。先后荣获四川省教学成果二等奖两项，南充市科技进步等奖1项，主讲的“实变函数”课程先后被评为四川省精品课程和四川省精品资源共享课程。

4）报告题目：Machine Learning and Dynamical Systems Meet in Reproducing Kernel Hilbert Spaces

报告人：Boumediene Hamzi（Johns Hopkins University）

报告时间：11月13日 16:45-17:15

报告摘要：

Since its inception in the 19th century through the efforts of Poincaré and Lyapunov, the theory of dynamical systems addresses the qualitative behavior of dynamical systems as understood from models. From this perspective, the modeling of dynamical processes in applications requires a detailed understanding of the processes to be analyzed. This deep understanding leads to a model, which is an approximation of the observed reality and is often expressed by a system of Ordinary/Partial, Underdetermined (Control), Deterministic/Stochastic differential or difference equations. While models are very precise for many processes, for some of the most challenging applications of dynamical systems, the development of such models is notably difficult. 

The intersection of the fields of dynamical systems and machine learning is largely unexplored and the objective of this talk is to show that working in reproducing kernel Hilbert spaces offers tools for a data-based theory of nonlinear dynamical systems. In this talk, we introduce the method of parametric and nonparametric kernel flows to predict some chaotic dynamical systems.  

报告人简介：

Boumediene is currently a visiting Professor at Johns Hopkins University and held many academic positions at UCDavis, the Mathematical Sciences Research Institute in Berkeley (CA), Duke University, Imperial College London, and  Caltech.  He is also an External Researcher of the Alan Turing Institute where he is co-leading the Research Interest Group (RIG) on Machine Learning and Dynamical Systems”.He worked on the ``Dynamical Theory of Control'' where the goal is the integration of concepts and ideas from dynamical systems theory and control theory into a framework that allows to develop both theories.  He particularly worked on the analysis and control of systems with bifurcations. His current research interests are at the intersection of Machine Learning and Dynamical Systems and especially the analysis of autonomous, control and random dynamical systems in Reproducing Kernel Hilbert Spaces in view of developing data-based methods for the analysis and prediction of random dynamical systems and  control strategies for nonlinear systems on the basis of observed data (rather than a pre-described model). He is  particularly interested in developing a qualitative theory for dynamical systems in reproducing kernel Hilbert spaces.

5）报告题目：Coordination estimation of enterprise resource planning and manufacturing execution system diffusion in China's manufacturing industry: a panel Lotka-Volterra method

报告人：王正新（浙江财经大学）

报告时间：11月12日 11:30-12:00

报告摘要：

The interaction between enterprise resource planning (ERP) and manufacturing execution system (MES) is an important way in which to realize the digital transformation and upgrading of Chinese enterprises. Based on the panel data pertaining to 31 provinces in China from 2011 to 2017, a panel discrete Lotka-Volterra model is established to estimate the relationship between ERP and MES markets. Interaction terms for time, region, and core variables are introduced to examine the heterogeneity of the relationship between ERP and MES. The results show that the market of ERP and MES for digital technology products in China presents a mutually beneficial and symbiotic relationship. However, there is the regional and temporal heterogeneity in the relationship. The effectiveness of the novel Lotka-Volterra model has been verified by its significant prediction accuracy and greatly enhanced robustness.

报告人简介：

王正新，江苏高邮人，2011年毕业于南京航空航天大学管理科学与工程专业，获管理学博士学位，现任浙江财经大学经济学院院长、教授、博士生导师。主要研究方向为经济预测与政策评估方法及应用，主持国家自然科学基金项目3项、国家自然科学基金重点项目和国家社科基金重大项目子课题2项，浙江省重大和重点项目2项。在Economics Letters、 Finance Research Letters 、Technological Forecasting & Social Change、《系统工程理论与实践》《中国管理科学》《计量经济学报》等国内外学术期刊发表论文70多篇。曾入选浙江省高校中青年学科带头人、浙江省之江青年拔尖学者、浙江省“万人计划”领军人才等人才工程，以及全球前2%顶尖科学家榜单。目前兼任中国数量经济学会常务理事，The Journal of Grey System、《复印报刊资料·国民经济管理》、《财经论丛》编委等学术职务。

6）报告题目：数据驱动下的灰调度模型与应用

报告人：谢乃明（南京航空航天大学）

报告时间：11月12日 11:00-11:30

报告摘要：

本研究聚焦灰色系统理论的核心问题，分享灰数的产生过程，灰数的比较与运算，以及灰数如何结合调度实际问题进行应用等关键问题，形成数据驱动下的灰调度解决方案。

报告人简介：

bat365中文官方网站副院长、教授、博士生导师；主要研究领域：灰色系统理论、运营系统优化、智能数据分析与高级计划排程；担任国际灰色系统与不确定性分析联合会秘书长、中国优选法统筹法与经济数学研究会理事和灰色系统专业委员会副理事长、江苏省机械工程学会工业工程专业委员会秘书长和Grey Systems: Theory and Application国际期刊副主编，主持国家自然科学基金项目5项、科技部、教育部、江苏省等省部级项目10余项。发表学术期刊论文100余篇（其中SCI、SSCI收录80篇）。获中国百篇最具影响国内学术论文奖（2008）、Applied Mathematical Modelling高被引论文奖（2011）、教育部自然科学奖二等奖（2012，排名第四）、江苏省科学技术奖一等奖（2015，排名第四）、教育部高等学校优秀人文社会科学研究奖三等奖（2015，排名第二）、教育部自然科学二等奖（2018，排名第四）、江苏高校哲学社科研究成果一等奖（2018，排名第一）。入选江苏省“青蓝工程”中青年学术带头人和江苏省第六批“333高层次人才培养计划”。入选全球前2%顶尖科学家榜单。

7）报告题目：中断航班恢复的灰色多目标模型

报告人：陈可嘉（福州大学）

报告时间：11月12日 14:00-14:30

报告摘要：

针对同时考虑灰色延误时间和灰色机场容量的多目标中断航班恢复问题，提出了一种灰色多目标规划模型，其目标函数为最小化航空公司总延误成本以及最小化旅客总延误时间。给出了基于上下界拆解的灰色模型转化方法，将灰色模型转化为可求解的确定模型。最后，通过福州国际机场的算例，验证了该转化方法处理中断航班恢复灰色多目标模型的优越性，使用ε约束法求解出多目标模型的Pareto最优解集。

报告人简介：

陈可嘉，教授、博士生导师。现任福州大学bat365中文官方网站副院长。兼任教育部工业工程类专业教学指导委员会委员，国家自然科学基金管理科学部评审专家，国家一流本科专业建设点“福州大学工业工程专业”负责人，福建省专业学位研究生联合培养示范基地“福大-冠捷工业工程实践基地”负责人，福建省专业学位研究生导师团队“工业与系统工程团队”负责人，SCI期刊JGS编委。主要从事运营管理、管理系统工程等方面的教学科研工作。近年来主持完成国家自然科学基金项目、国家社会科学基金项目等科研课题30余项、省部级以上教改课题10余项；正式出版专著1部、教材1部；发表学术论文100余篇；获得省级优秀成果奖2项、国际会议优秀论文奖4项、省级优秀教学成果奖1项。入选首批“福建省高校杰出青年科研人才培育计划”、“教育部新世纪优秀人才支持计划”。

8）报告题目：灰色系统理论在水利工程建设管理中的应用与创新

报告人：张可（河海大学）

报告时间：11月12日 14:30-15:00

报告摘要：

近年来，我国全力加快水利基础设施建设，水利工程建设和运行管理任务重，如何提高工程管理效能是迫切需要解决的问题。首先，系统性分析灰色系统理论在水利工程管理中的实践经验、应用成果。然后，分析水利工程中项目管理、市场管理两个层次的业务，及其存在的少数据、异构数据、非等长数据等特征和数据分析、建模需求。其次，针对管理实际需求，探讨非等长、序数型、异构性数据的灰色建模方法。最后，对水利工程建设管理的数据分析进行总结和展望。

报告人简介：

近年来在国内外学术期刊发表论文30余篇，主持或参与国家级、省级项目15项，作为主要完成人获得2016年国防科技进步一等奖、2018年江苏省哲学社会科学二等奖、2020年教育部哲学社会科学二等奖、2018年江苏省高校哲学社会科学优秀成果一等奖，2017年IEEE GSIS国际会议优秀论文奖、2018年Emerald优秀论文奖。主编了《浙江省水利工程质量监督工作实务》；参与编制《水利工程建设项目管理总承包管理规范》团体标准。

9）报告题目：基于直觉灰数集的一般灰数决策模型及其应用

报告人：蒋诗泉

报告时间：11月12日 15:00-15:30

报告摘要：

主要针对决策信息为一般灰数时，由于一般灰数运算法则和排序还不够完善这一现状，为了提高决策精度，首先，将直觉模糊方法和灰数的“核”与“灰度”方法集成，利用灰数可能度函数，定义了直觉灰数和直觉灰数集。其次，将一般灰数中每个小区间灰数用一个直觉灰数来表征，并将一般灰数转为一个直觉灰数集（或者将一般灰数转化为一个区间直觉灰数。）。最后，将两个一般灰数的运算定义为直觉灰数集之间的运算，并给出基于直觉灰数集的一般灰数的距离测度（或者将两个一般灰数的运算定义为区间直觉灰数之间的运算，并给出基于区间直觉灰数的一般灰数的距离公式。）在此基础上给出灰色决策模型，算例表明该方法是合理有效的。

报告人简介：

蒋诗泉，安徽舒城县人，教授，博士，硕士生导师，安徽省教学名师，现任铜陵学院教务处处长。入选安徽省高校学科（专业）拔尖人才、“数学建模”省级高水平教学团队负责人、铜陵学院“翠湖领军人才”、铜陵学院学术带头人、铜陵学院科研创新团队负责人。近年来，主持省部级科研项目4项、市厅级项目6项。主持省级质量工程4项、高水平教学团队一个。多次获得安徽省教学成果二等奖(排名第一)。在国内外核心期刊上发表论文30余篇、出版学术专著1部、主编教材1部。主要研究领域：灰色系统理论、复杂系统建模、不确定性理论。

10）报告题目：一种新的季节灰色预测模型及其应用

报告人：李晔（河南农业大学）

报告时间：11月12日 15:50-16:20 

报告摘要：

针对含长期趋势性、季度波动性和随机非线性等复杂特征的小样本序列预测问题，提出一种新的季节灰色预测模型，即 模型。首先，将三角函数和时变参数组合纳入含时间幂次项的非线性灰色模型( )中，构造 模型；然后，采用调试法和遗传算法分别确定时间延迟参数和非线性参数的最优值；最后，将模型应用于我国季度用电量的预测研究，结果表明，该模型能有效描述序列的非线性和季度性。进一步进行样本外预测，结果显示，该模型具有较高的精度，MAPE仅为2.72%。预测结果可以为电力企业和有关政府部门的高效决策提供数据支持。

报告人简介：

李晔，女，1972年5月出生，河南南阳人，中共党员，三级教授，硕士生导师，河南农业大学信息与管理科学学院副院长。教育部第五轮学科评估网评专家，河南省教科文卫体系统秀教师，中国灰色系统专业委员会常务理事，中国农业系统工程专业委员会常务理事，SCI期刊《The Journal of Grey System》编委。主要研究方向：灰色系统理论及其应用，农产品物流及供应链管理。承担完成国家自然基金、河南省科技厅软科学项目、河南省高等学校重点科研项目、河南省高等学校人文社科重点项目等科研项目20项，第一或通讯作者发表核心期刊以上论文80余篇，出版专著或教材7部，荣获河南省优秀教学成果二等奖一项、河南省科技进步三等奖一项。主讲课程：灰色系统、管理学原理、管理经济学、管理科学与工程专题。

11）报告题目：多维灰色模型的研究进展及发展趋势思考

报告人：郭欢（江汉大学）

报告时间：11月12日 16:20-16:50 

报告摘要：

从1982年邓聚龙教授提出灰色模型开始讲起，回望40年来多维灰色模型的发展历程，综述目前多维灰色模型的研究现状，探讨未来多维灰色模型的研究方向。

报告人简介：

郭欢，博士，副教授，江汉大学人工智能学院副院长。主要研究方向为灰色系统理论与应用、系统控制与优化。主持国家自然科学基金项目、湖北省自然科学基金项目、中国博士后基金项目等多项，发表学术论文二十余篇。

12）报告题目：灰色预测模型的数理基础

报告人：韦保磊（南京理工大学）

报告时间：11月12日 16:50-17:20

报告摘要：

灰色预测模型是灰色系统理论的主要组成部分, 其以累加生成算子为标志性工具. 本汇报从累加生成算子出发, 结合描述模型动态方程的形式, 解析灰色预测模型的数理基础, 主要包括累加生成算子与积分算子的关系解析、线性模型的积分方程统一与约简, 非线性模型的积分-微分方程统一与约简等。

报告人简介：

2021年于南京航空航天大学管理科学与工程专业获博士学位, 现为南京理工大学经济管理学院讲师. 主要研究方向为灰色系统理论、动力系统和机器学习, 累积发表相关SCI论文10多篇。

13）报告题目：Dynamic Grey Relational Analysis

报告人：Saad Ahmed Javed （the International Journal of Grey Systems (IJGS)、Grey Systems Society of Pakistan (GSSP)）

报告时间：11月13日 14:30-15:00

报告摘要：

In the 1980s, Professor Deng Julong proposed the first Grey Relational Analysis (GRA) model and enriched the Grey System Theory with a powerful technique. In succeeding years, Deng’s GRA was used for multiple-criteria decision-making (MCDM), data clustering, optimization of parameters (such as in manufacturing engineering), and evaluating the relationship between different variables (such as in economics), among others. In Deng’s GRA, a parameter called Distinguishing Coefficient is generally estimated subjectively; thus, the analysis results are only approximately accurate. The Dynamic GRA is a generalized form of Deng’s GRA. By estimating the ‘Dynamic’ Distinguishing Coefficient precisely and enabling the use of the raw data directly without its normalization, the Dynamic GRA provides an effective and efficient technique for decision-making. The current lecture presents the theory, method, and application of the Dynamic GRA. Some new properties of the GRA are also introduced.  

报告人简介：

Saad Ahmed Javed is the chief editor of the International Journal of Grey Systems (IJGS), and President of the Grey Systems Society of Pakistan (GSSP). He earned a PhD in Management Science and Engineering and MS in Project Management. The 2022 Stanford/Elsevier report listed him among the top 2% scientists in three categories (AI, ICT, and, Business and Management). He and/or his works have been quoted/cited by Nature, Nature Index, Transparency International, and MSN News, among others. Currently, he teaches in a public university in Nanjing. He is primarily known for his works on Bidirectional and Dynamic Grey Relational Analyses models, Optimized Grey Forecasting, and Grey Ordinal Priority Approach. He can be contacted at drsaj@nuist.edu.cn, while his works can be read at www.GreySystem.org.   

14）报告题目：40 Years of Grey Systems Theory in Economics and Social Sciences

报告人：Camelia Delcea（Bucharest University of Economic Studies）

报告时间：11月13日 15:00-15:30

报告摘要：

Since 1982, when the first description of the grey systems has been provided by Professor Deng, the grey systems theory has produced tremendous changes to all the research area in which it has successfully been applied. The change of paradigm brought by the grey numbers has revolutionized the way we interact with numbers and with the information within them. Nevertheless, the new methods included under the grey systems theory umbrella and particularly designed to deal with the grey numbers have provided the needed means to better understand the complex world we are living in and to address its everyday issues and challenges. In this context, the economic and social sciences field has benefit from the advancements made by the grey systems theory in the last 40 years and so did many other scientific fields. The benefits have been both theoretical – by providing new ways of addressing classical economic and social sciences problems, and practical – by offering sharp solutions to difficult-to solve problems generated by the dynamicity of the economic and social environment. Thus, let us explore together and discuss how the 40-years of grey systems theory changed irreversibly the economic and social sciences field through the use of a bibliometric analysis. 

报告人简介：

Dr. Delcea is an active member in the area of grey systems theory, agent-based modeling and sentiment analysis.  Since 2009, Dr. Delcea has obtained 25 international and national awards (“Best paper award”, “Georgescu Roegen” for excellent scientific research, “Excellent paper award”,“Top reviewers”, etc.). Currently she serves as Editorial Board Member for  Grey Systems: Theory and Application and she is Associate Editor for IEEE Access, Plos One and Advances in Civil Engineering.

15）报告题目：Human-centred AI and Grey Data

报告人：Yingjie Yang（英国德蒙福特大学）

报告时间：11月13日 15:30-16:00

报告摘要：

This talk will discuss the requirement of human-centred AI and its related challenge for grey data research.  Due to the involvement of human, cognition perception and uncertainty are the central challenge for Human-centred AI.  The communication between human and machine determines the success of human-centred AI.  Therefore, an effective grey data representation and interpretation is crucial for such systems.  We will discuss issues related with this data representations and interpretations. 

报告人简介：

杨英杰教授，现任英国得蒙福特大学计算智能教授、人工智能研究所所长，兼任国际灰色系统与不确定性分析学会执行主席、IEEE计算智能学会模糊系统竞赛委员会副主席和IEEE灰色系统技术委员会共同主席，同时，还担任国际期刊”Journal of Grey Systems 和 Grey Systems: Theory and Application的副主编，长期从事计算智能和不确定性系统研究，在灰色系统、模糊逻辑、神经网络、数据挖掘、商业智能和复杂装备研制管理领域，积累了丰富的研究基础。杨教授近年来承担欧盟委员会第6研究框架、第7研究框架、欧洲空间局(ESA)、英国皇家学会, 英国工程和自然科学研究委员会(EPSRC)、皇家工程院等委托课题15项，总经费超过100万英镑，发表学术论文120多篇。

16）报告题目：Tentative application of grey system theory for manufacturing optimization and assembly operation recognition

报告人：Yicha Zhang（法国国立贝尔福-蒙贝利亚工程技术大学）

报告时间：11月13日 16:15-16:45

报告摘要：

Although big data technologies show great potential in manufacturing data processing and decision-making, there are still many difficulties to apply such king of tools since some manufacturing data sets are hard to obtain in a large quantity due high cost. On the other hand, for some special applications, when the accuracy is not the priority but computation efficiency is more important, classical mathematical modeling tools may gain advantage as compared to big data processing tools. With this regard, grey system theory, a tool for less data modeling, may bring a different solution. In this talk, two tentative application examples of grey system theory for manufacturing process modeling and assembly operation recognition will be presented for performance demonstration and open discussion.  

报告人简介：

张益茬，法国国立贝尔福-蒙贝利亚工程技术大学（UTBM）机械设计与工程系副教授，在法国科学研究中心交叉科学研究院联合实验室(CNRS, ICB-COMM) 研究部主要研究面向增材制造的设计与工艺规划基础理论，开发通用的服务于智能增材制造的工艺规划专家系统原型。先后参与欧盟第7框架项目与H2020地平线项目，主持法国国家研究署优秀青年独立研究基金（ANR JCJC）、法国东部地区青年独立研究基金（UBFC-ANER）以及东部地区联合基金等多项科研项目，获得科研经费累计超过129万欧元。在设计与制造领域发表研究论文80余篇、获软件著作权和专利10余项、期刊论文奖3次。2020年8月被国际生产工程研究院（CIRP）提名为通信会员（Associate Member），2021年8月获CIRP青年学术奖章（CIRP Taylor Medal）。

17）报告题目：Review of the Philosophical and Conceptual Foundations of Grey Systems Theory

报告人：Ehsan

报告时间：11月12日 13:30-14:00

报告摘要：

Every scientific or intellectual movement rests on central premises and assumptions that shape its philosophy. The purpose is to review a brief account of the main philosophical bases of grey systems theory (GST) and the paradigm governing its principles. So, the recent studies on the philosophical foundations of GST have been reviewed and tried to pay attention to some key ambiguities in the previous studies and give more and clearer explanations. Also, the study tries to fill the gap among the previous studies and to provide a purposeful connection between them by expressing two key concepts: complete information and imbalanced knowledge. Primarily, the study addresses the theoretical foundations of uncertainty and the concept of greyness. Next, it focuses on the notion of “complete information” and the challenges to it. Then, it reviews such processes as perception, cognition, and understanding, as well as their dynamic nature. It explains how knowledge is produced through understanding and interpreting information/data and the dynamics governing the whole process. Also, the study describes any dataset, no matter how large it may be, will remain incomplete, imperfect, and grey, so humans only rely on incomplete datasets to interpret the world. As such, information and knowledge are always grey and uncertain because they are basically contingent on subjective understandings and interpretations and imperfect inputs and data. Finally, as a key development, this study also demonstrates that human grey knowledge remains imbalanced across different disciplines and spheres. In the end, a brief overview of the philosophical paradigm of GST is also provided. GST is depicted as an anti-realistic, anti-positivistic, and non-deterministic approach, which is inherently pluralistic and ideographic. According to GST principles, dynamicity and change are essential parts of human narratives of the world and systems, and human knowledge is constantly reproduced through collecting new information. As a result, knowledge, theories, narratives, and scientific laws dynamically change. Given this premise, one could argue that GST is considerably compatible with the postulates of post-modern thinking.

报告人简介：

Ehsan Javanmardi is an associate professor in the College of Economics and Management, Nanjing University of Aeronautics and Astronautics (NUAA), Nanjing, China. Before, he was a postdoctoral researcher at NUAA from 2018 to 2020. He has also collaborated as a researcher with the faculty of informatics and management at the University of Hradec Kralove, Czech Republic for three years. He received his M.S. degree in Industrial Engineering from the Iran University of Science and Technology (IUST), Tehran, Iran, in 2009. Also, He obtained his Ph.D. degree in Systems Management from Shiraz University, Shiraz, Iran, in 2016. As well as, he is a member of the Editorial Advisory Board of the Journal Grey Systems: Theory and Application (SCI). He is also a full-time faculty of the Institute of Grey Systems, Nanjing, China. His current research interests include grey systems theory, Socio-Economic Systems, and System Dynamics.

18）报告题目：R-fuzzy Sets and Grey Theory

报告人：Arjab Singh Khuman（De Montfort University）

报告时间：11月13日 17:15-17:45

报告摘要：

The notion of grey theory to some may seem foreign and rather alien to some, however, it is aspects of grey theory that have allowed for my research to link together the subjective nature of perception based uncertainty, to that of objective based inference. The functionality of grey theory lends itself quite well to be hybridised with other existing concepts. My research is predominately associated to the quantification of subjective based uncertainty, which in of itself can be rather uncertain. When considering a snapshot of information, one is faced with the issue of maintaining the information and sentiment captured from said snapshot. If the information is subjective, it needs to be observed from an objective means to provide for a detailed inference which can be repeated and contrasted. The use of R-fuzzy sets in capturing uncertainty is paramount to my research, for no information is lost and all the nuances that are observed are preserved in the membership sets. The problem is now linking it to the likes of grey incidence analysis, for it is this component of grey theory that provides a metric based on inference between two comparable sequences. It is only with the use of my significance measure that we can bridge together R-fuzzy’s uncertainty handling capabilities to that of the inference of grey’s incidence analysis, in doing so, providing a similarity index, from which greater detail can be garnered and ergo, a more detailed response given. The result is the R-fuzzy Grey Analysis framework (RfGAf), a framework that is highly applicable, versatile and robust.

报告人简介：

Award winning lecturer and internationally renowned researcher, recipient of multiple Vice Chancellor’s Distinguished Teaching Awards (VCDTAs) [2018, 2019 & 2021]. Awarded a De Montfort Teacher Fellowship Award (2022) in recognition of my teaching excellence. Senior Fellow of the Higher Education Academy (SFHEA) in recognition of my influence and leadership within the Higher Education sector. Experienced leadership of some of the more complex programmes and modules belonging to the faculty of Computing, Engineering and Media (CEM) and Institute of Artificial Intelligence (IAI). Involved with the creation of considerable outreach activities; Summer Schools; Knowledge Transfer Partnerships; Industrial Projects; Showcases and Global Engagements. Contributed heavily to the research output of the School. Secured a British Computer Society (BCS) accreditation for the Artificial Intelligence programme, with exceptional commendations. Pioneered the Peer Assisted Learning Scheme (PALS) to high acclaim, commendation to be shared throughout the institute. Successful implementation of change, embedded best practice to support transitions that address the need of a diverse student body. Advisory member to the Centre for Academic Innovation (CAI); the Pedagogic Interest Group (PIG); Student Experience and Engagement (SEE); co-chair of the Race Equality Network (REN); and various other working groups and committees. Collaborations with School groupings to monitor quality & relevance of curricula. Facilitate student input and contribution to foster academic community and enable all students to have an exceptional university experience, to be as appealing and applicable as possible.