Professor Yingjie Yang

Job: Professor of Computational Intelligence

Faculty: Technology

School/department: School of Computer Science and Informatics

Research group(s): Centre for Computational Intelligence (CCI) and De Montfort University Interdisciplinary Group in Intelligent Transport Systems (DIGITS)

Address: De Montfort University, The Gateway, Leicester, LE1 9BH, United Kingdom

T: +44 (0)116 257 7939

E: yyang@dmu.ac.uk

W: http://www.dmu.ac.uk/cci

 

Personal profile

Dr. Yingjie Yang was awarded his first PhD in Engineering from Northeastern University in 1994, and his second PhD in Computer Science in 2008. He has published more than 100 papers in international journals and conferences. He has been involved in more than 90 international conferences as a member of program committees and organised a number of international conferences and special sessions such as 2015 IEEE International Conference on Grey Systems and Intelligent Service, IEEE SMC 2014 and IEEE WCCI2008. As a senior member of IEEE, Dr. Yang serves as a co-chair of the Technical Committee on Grey Systems, IEEE Systems, Man and Cybernetics Society and the vice chair for the task force for competition in IEEE Fuzzy Systems Technical Committee. He is serving also as an associate editor for 5 international academic journals, including IEEE Transactions on Cybernetics. He had been invited to give plenary speech at a number of international confertences, such as the 2013, 2011 and 2009 IEEE Conferences on Grey Systems and Intelligent Services and the 2001 international conference on Airport Management.

Publications and outputs 

  • Multiagent Collaborative Governance for Targeted Poverty Alleviation from the Perspective of Stakeholders
    Multiagent Collaborative Governance for Targeted Poverty Alleviation from the Perspective of Stakeholders Zhang, Na; Xiangxiang, Zhang; Lei, Ming; Yang, Yingjie As a social problem involving a wide range of objects, targeted poverty alleviation governance needs to clearly define stakeholders and identify their behaviour choices, so as to seek a multiagent collaborative governance strategy, and strive to jointly promote the realization of a targeted poverty alleviation goals in an atmosphere to win-win cooperation and benefit sharing. By constructing a three-subject evolutionary game model of local government, social organization, and poverty group in the process of targeted poverty alleviation, this paper discusses the influence of their behavioural decisions on multisubject collaborative governance of targeted poverty alleviation and selects samples to carry out simulation experiments on the model. The results show that, first, superior government support has little effect on the evolution of tripartite competition, and the conclusion is inconsistent with the general cognition. However, the enhancement of support from local governments and social organizations can effectively promote the transformation of the willingness of the poor groups to cooperate. Second, a modest increase in the punishment of social organizations and poor groups can have a binding effect on the behavioural strategy choices of both sides and ultimately promote the process of targeted poverty alleviation. Third, the increase in the benefits of social organizations and poor groups can significantly improve the willingness of both sides to cooperate, so the “endogenous driving force” of the poor groups should be enhanced to achieve the Pareto optimal state of targeted poverty alleviation. open access article
  • Weight Analysis for Multiattribute Group Decision-Making with Interval Grey Numbers Based on Decision-Makers’ Psychological Criteria
    Weight Analysis for Multiattribute Group Decision-Making with Interval Grey Numbers Based on Decision-Makers’ Psychological Criteria Guo, Sandang; Junjuan, Liu; Yang, Yingjie To address the problem of multiattribute group decision-making with interval grey numbers, decision matrices are adjusted using kernels of interval grey numbers to reduce the psychological effects of decision-makers. The comprehensive weights of attributes are obtained by aggregating the subjective weights with objective weights, which are calculated based on the accuracy and difference of attributes. Considering the consistent, best, and worst decision-making abilities of decision-makers, grey incidence models are established to obtain the consistency weights and individual bipolar weights of decision-makers; then, the comprehensive weights of decision-makers are determined. A clustering approach of interval grey numbers is presented, and overall evaluations are obtained. Finally, an example is provided and its validity is tested to verify the feasibility of the proposed method. open access article
  • Filter Design for Positive T-S Fuzzy Continuous-Time Systems with Time Delay Using Piecewise-Linear Membership Functions
    Filter Design for Positive T-S Fuzzy Continuous-Time Systems with Time Delay Using Piecewise-Linear Membership Functions Meng, Aiwen; Lam, Hak-Keung; Liu, Fucai; Yang, Yingjie This work focuses on the filtering problem and stability analysis for positive Takagi-Sugeno (T-S) fuzzy systems with time delay under L1-induced performance. Due to the importance of estimation of system states but the few filter design results on positive nonlinear systems, it is an attractive and meaningful topic well worth studying. In order to fully exploit and take advantage of the positivity of positive T-S fuzzy systems, many commonly used methods, for instance free-weighting matrix approach and similarity transformation are probably not suitable for positive systems. To address the hard-nut-to-crack problem, an auxiliary variable is introduced so that the augmentation approach can be employed to carry out the positivity and stability analysis of filtering error systems. In addition, another obstacle that cannot be ignored is the existence of non-convex terms in the stability and positivity conditions. For getting around this barrier, some iterative linear matrix inequality (ILMI) algorithms have been proposed in the literature. However, considering the weakness that these methods cannot guarantee the convergence to a numerical solution and the iterative process is exhaustive, we present an effective matrix decoupling method to convert the nonconvex conditions into convex ones in this paper. Furthermore, a linear co-positive Lyapunov function which incorporates the positivity of system states and time delay at the same time is chosen so that the positivity characteristic of filtering error systems can be captured further. However, because of plenty of valuable information of membership functions (MFs) being ignored, hence, the obtained results are conservative. For the sake of relaxing the conservativeness, the advanced piecewise-linear membership functions (PLMFs) approximate method is utilized to facilitate the stability and positivity analysis. Therefore, the relaxed stability and positivity conditions which are cast as sum of squares (SOS) are obtained and can be solved numerically. Finally, the effectiveness of the designed fuzzy filtering strategy with satisfying L1-induced performance are demonstrated by a simulation example. The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.
  • Game Analysis on the Evolution of Decision-Making of Vaccine Manufacturing Enterprises under the Government Regulation Model
    Game Analysis on the Evolution of Decision-Making of Vaccine Manufacturing Enterprises under the Government Regulation Model Zhang, Na; Yang, Yingjie; Wang, Xiaodong; Wang, Xinfeng The harm caused by defective vaccines to human health and social stability is immeasurable. Aiming at the government’s supervision of the vaccine market, an evolutionary game model is constructed to analyze the quality of supervision and the key factors in the dynamic interaction between government departments and vaccine manufacturers under different supervision modes in the vaccine manufacturing process. The results show that: (1) Severe punishment by government regulatory authorities, and increased costs of rectification after investigation and handling of involuntary behaviors of vaccine enterprises can effectively prevent involuntary behaviors of vaccine enterprises. (2) In the early stage of the game, the success rate of the government’s efficient supervision will make the vaccine enterprises continuously self-disciplined; when the vaccine market is relatively stable, the government’s supervision departments tend to be more conducive to passive supervision. (3) The success rate of government regulatory departments and the probability of a third-party reporting to play a great role in promoting the self-discipline of enterprises. (4) The power of government and regulation are conducive to promoting the active supervision of the government regulatory authorities but corruption of government and awareness of people are different. Once the phenomenon of vaccine enterprises’ non-discipline increases, the government regulation must change from passive regulation to active regulation. Therefore, the government should implement different measures according to the characteristics of each period in the manufacturing process to effectively prevent problematic vaccines. The conclusions and policy recommendations are significant for addressing the issue of insufficient self-discipline of vaccine manufacturers. open access article
  • Hybrid genetic algorithm based on bin packing strategy for the unrelated parallel workgroup scheduling problem
    Hybrid genetic algorithm based on bin packing strategy for the unrelated parallel workgroup scheduling problem Su, Bentao; Xie, Naiming; Yang, Yingjie In this paper we focus on an unrelated parallel workgroup scheduling problem where each workgroup is composed of a number of personnel with similar work skills which has eligibility and human resource constraints. The most difference from the general unrelated parallel machine scheduling with resource constraints is that one workgroup can process multiple jobs at a time as long as the resources are available, which means that a feasible scheduling scheme is impossible to get if we consider the processing sequence of jobs only in time dimension. We construct this problem as an integer programming model with the objective of minimizing makespan. As it is incapable to get the optimal solution in the acceptable time for the presented model by exact algorithm, meta-heuristic is considered to design. A pure genetic algorithm based on special coding design is proposed firstly. Then a hybrid genetic algorithm based on bin packing strategy is further developed by the consideration of transforming the single workgroup scheduling to a strip-packing problem. Finally, the proposed algorithms, together with exact approach, are tested at different size of instances. Results demonstrate that the proposed hybrid genetic algorithm shows the effective performance. The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.
  • A greyness reduction framework for prediction of grey heterogeneous data
    A greyness reduction framework for prediction of grey heterogeneous data Li, Chong; Yang, Yingjie; Liu, Sifeng Existing operational rules of interval grey numbers do not make full use of possible background information when determining the interval boundaries, and this may result in inconsistent results if applying different logical operations. This paper finds that multiplication and division rules of interval grey numbers do not meet the calculation rule of inverse operators. Direct solution and inverse solution of the same interval grey number object may differ not only in numerical ranges but also in greyness degrees. To improve the accuracy of grey number calculation, new operational rules for multiplication and division of interval grey numbers are proposed. Then the traditional prediction modeling method of grey heterogeneous data is refined and expanded by integrating a greyness reduction preprocessing, which is based on the proposed calculation rules. Application of the expanded heterogeneous interval grey number prediction model to a stock replenishment scheduling problem in emergency rescue scenarios is included to illustrate the new operational rules of grey numbers and their application in prediction algorithm, and the proposed approach is compared with other existing methods to demonstrate its effectiveness. The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.
  • Study on mechanism and filter efficacy of AGO/IAGO in the frequency domain
    Study on mechanism and filter efficacy of AGO/IAGO in the frequency domain Lin, Changhai; Song, Zhengyu; Liu, Sifeng; Yang, Yingjie; Forrest, Jeffrey Purpose – The purpose of this paper is to analyze the mechanism and filter efficacy of accumulation generation operator (AGO)/inverse accumulation generation operator (IAGO) in the frequency domain. Design/methodology/approach – The AGO/IAGO in time domain will be transferred to the frequency domain by the Fourier transform. Based on the consistency of the mathematical expressions of the AGO/ IAGO in the gray system and the digital filter in digital signal processing, the equivalent filter model of the AGO/IAGO is established. The unique methods in digital signal processing systems “spectrum analysis” of AGO/IAGO are carried out in the frequency domain. Findings – Through the theoretical study and practical example, benefit of spectrum analysis is explained, and the mechanism and filter efficacy of AGO/IAGO are quantitatively analyzed. The study indicated that the AGO is particularly suitable to act on the system’s behavior time series in which the long period parts is the main factor. The acted sequence has good effect of noise immunity. Practical implications – The AGO/IAGO has a wonderful effect on the processing of some statistical data, e.g. most of the statistical data related to economic growth, crop production, climate and atmospheric changes are mainly affected by long period factors (i.e. low-frequency data), and most of the disturbances are shortperiod factors (high-frequency data). After processing by the 1-AGO, its high frequency content is suppressed, and its low frequency content is amplified. In terms of information theory, this two-way effect improves the signal-to-noise ratio greatly and reduces the proportion of noise/interference in the new sequence. Based on 1- AGO acting, the information mining and extrapolation prediction will have a good effect. Originality/value – The authors find that 1-AGO has a wonderful effect on the processing of data sequence. When the 1-AGO acts on a data sequence X, its low-pass filtering effect will benefit the information fluctuations removing and high-frequency noise/interference reduction, so the data shows a clear exponential change trends. However, it is not suitable for excessive use because its equivalent filter has poles at the non-periodic content. But, because of pol effect at zero frequency, the 1-AGO will greatly amplify the low-frequency information parts and suppress the high-frequency parts in the information at the same time. The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.
  • A Novel Synthetic Index of Two Counts and Mathematical Model for Researcher Evaluation
    A Novel Synthetic Index of Two Counts and Mathematical Model for Researcher Evaluation Liu, Sifeng; Li, Qi; Yang, Yingjie Purpose – The purpose of this paper is to present a novel synthetic index of two counts and mathematical model for researcher evaluation. Design/methodology/approach –A synthetic index L for researcher evaluation considering both the total number of other citations (C) and non-academic impact (I), and a synthetic evaluation model is proposed in this paper. C and I are verified impact indexes. According to investigation by Delphi method, researchers are divided into five different classes of “below average”, “average”, “good”, “excellent” and “stellar”. The threshold values for counts C of grey class “stellar” are determined by deep investigation. The possibility functions of the two counts C and I on four grey classes of “below average”, “average”, “good”, and “excellent” are built. Findings –The novel synthetic index of two counts and mathematical model for researcher evaluation providing a better way to conduct researcher assessment. Practical implications –The synthetic index L presented in this paper can be used to evaluate a researcher. It’s more reasonable than the current research assessment indexes such as the number of publications and the numbers of so called high quality journal publications, and the amount of granted funds, etc. The synthetic index L reflect the actual value created by a researcher. No artificial manoeuvre can change them significantly. Originality/value –A synthetic index L for researcher evaluation considering both the total number of other citations (C) and non-academic impact (I), and a synthetic evaluation model is proposed in this paper. The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.
  • A Business Process Oriented Dynamic Cyber Threat Intelligence Model
    A Business Process Oriented Dynamic Cyber Threat Intelligence Model Xu, Yuanchen; Yang, Yingjie; He, Ying Cyber threat intelligence (CTI) is a method for strengthening information security. CTI provides information on threats and the countermeasures. Businesses can benefit from the defensive knowledge if the relevant CTI is found. However, business environments involve miscellaneous dynamics of the business processes that can dynamically change the contexts. Correspondingly, threats associated with the contextual risk factors can change dynamically at the same time. Every time the contextual changes take place, CTI-based defensive strategies for businesses may not be useful and effective any more. However, the existing connection strategies between CTI and business risk contexts are still somewhat static. This paper proposes a business process oriented dynamic CTI model. The model can observe and capture the dynamics from the business environments. Every time the dynamics are captured, the model will then trigger adjustments of the connection strategies within the model. We use a case study to illustrate the use of the model and present how the model adjusts the connection strategies according to the dynamics. We then conclude the paper with future directions of the research. The Publisher's final version can be found by following the DOI link.
  • Predict the particulate matter concentrations in 128 cities of China
    Predict the particulate matter concentrations in 128 cities of China Meng, Dun; Xu, Zhicun; Wu, Lifeng; Yang, Yingjie To predict the concentrations of PM2.5 and PM10 in the 128 cities of China, the discrete grey prediction model with fractional order accumulation (DFGM(1,1)) was used to predict the annual average PM2.5 and PM10 concentrations from 2019 to 2023. The result is as following: the annual average PM2.5 concentrations of Xi'an, Xuzhou, Ordos, Jingmen, Meizhou, Huizhou, Panzhihua, Kunming, Jixi and Yichun are increasing from 2019 to 2023. The annual average PM2.5 concentrations in the 118 other cities are decreasing from 2019 to 2023. While the annual average PM10 concentrations of Taiyuan, Ordos, Dongguan, Karamay, Foshan, Yichun, Qitaihe, Jinzhou and Heihe are increasing from 2019 to 2023. The annual average PM10 concentrations in the 119 other cities are decreasing from 2019 to 2023. The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.

Click here to view a full listing of Yingjie Yang's publications and outputs.

Key research outputs

  • R-Fuzzy sets: a novel combination of fuzzy sets with rough sets with capability to represent some situations difficult with other extensions;
  • Grey sets: a formal formulation of the concept of grey sets and its operations;
  • Relative Strength of Effect: a factor analysis method based on trained neural networks;
  • Application of neural networks in overlay operation of GIS
  • Airport noise simulation using neural networks

Research interests/expertise

Dr. Yang’s research interests are mainly with uncertainty models and their applications. His theoretical work involves fuzzy sets, rough sets, grey systems and neural networks. In applications, his interests are transportation planning, environment evaluation and civil engineering simulation and analysis.

Areas of teaching

  • Databases
  • Data Warehousing
  • AI programming

Qualifications

  • PhD in Engineering (1994 from Northeastern University, China)
  • PhD in Computer Science (2008 from Loughborough University, UK)

Courses taught

  • IMAT5167
  • IMAT5118
  • IMAT5103
  • IMAT2427
  • PHAR5350

Honours and awards

Best Paper Award, the 2013 IEEE Conference on Computational Intelligenceand Computing Research.

Membership of external committees

  • Co-chair of the Technical Committee on Grey Systems of IEEE Systems, Man,and Cybernetics Society, 2012 -- present
  • Vice-chair of the Task Force on Competitions for Fuzzy Systems Technical Committeeof IEEE Computational Intelligence Society, 2011 -- present
  • PC members for over 90 international academic conferences

Membership of professional associations and societies

  • Senior Member of IEEE, 2013 -- present
  • Member of IEEE, Mar 2007 -- 2013
  • Member of the Rail Research UK Association, May 2013 -- present

Current research students

First supervisor for:

  • Manal Alghieth
  • Mohammad Al Azawi
  • Arjab Khuman
  • Nguyen Thi Mai Phuong
  • Tarjana Yagnik

Externally funded research grants information

    • "International Network on Grey Systems and its Applications", Leverhulme Trust, PI, £124997, 2015--2018.

    • "Grey Systems and Its Application to Data Mining and Decision Support", EU FP7 Marie Curie International IncomingFellowship, PI, €309235, 2015--2016.

    • "Modeling Conditions, Mechanism and Characters of Grey Prediction Model GM(1,1)", Leverhulme Trust InternationalVisiting Fellowship, PI, £25500, 2013--2014.

    • "Grey Systems and Computational Intelligence", Royal Society, PI, £12000, 2011-- 2013.

    • "ITRAQ: Integrated Traffic Management and Air Quality Control Using Space Services", Europe Space Agency, CI, €97834, 2011--2012.

    • "Conference grant", Royal Academy of Engineering, PI, £500, Oct 2007.

Internally funded research project information

  • "Project application on Grey Systems and Uncertainty", DMU Research Leave scheme, PI, £7104, 2012--2013.

  • "Initial preparation for EU research network on grey systems", DMU RIF Fund, PI, £7000, 2011--2012.

  • "Emerging uncertainty models and their applications", DMU PhD scholarship, PI, £55080, 2012--2016.

  • "Conference grant", DMU RITI Fund, PI, £1500, Jun 2009.

  • "Conference grant", DMU RITI Fund, PI, £1500, Jun 2008.

Professional esteem indicators

Editorial board:

  • Associate Editor of IEEE Transaction on Cybernetics (Institute of Electrical and Electronics Engineers) ISSN: 1083-4419
  • Associate Editor of Scientific World Journal (Hindawi Publishing Corporation) ISSN: 2356-6140
  • Associate Editor of Journal of Intelligent and Fuzzy Systems (IOS Press) ISSN: 1064-1246
  • Assocaite Editor of Journal of Grey Systems (Research Information Ltd) ISSN: 0957-3720
  • Associated Editor of Grey Systems: Theory and Applications (Emerald) ISSN: 2043-9377

Plenary talks and academic seminars

  • Keynote speaker at the 2013 IEEE International Conference on Grey Systems and Intelligent Services, Macau, 2013
  • Seminar on grey numbers at Nanjing University of Aeronautics and Astronautics, Nanjing, 2012
  • Keynote speaker at the 2011 IEEE International Conference on Grey Systems and Intelligent Services, Nanjing,2011
  • Seminar on grey numbers at Nanjing University of Aeronautics and Astronautics, Nanjing, 2011
  • Seminar series on computational intelligence at Nanjing University of Aeronautics and Astronautics, full financialsupport from Nanjing University of Aeronautics and Astronautics, Nanjing, 2010
  • Keynote speaker at the 2009 IEEE International Conference on Grey Systems and Intelligent Services, Nanjing,2009
  • Seminar on grey systems at University of Hull, 2008
  • Keynote speaker at the Airport Environmental Management Workshop in Singapore, full financial support fromSingapore Aviation Academy (organisor), Singapore, 2001

Conference management

  • Chair of the Program Committee for the 2015 IEEE International Conference on Grey Systems and Intelligent Services,Leicester, 2015
  • Chair of the Program Committee for the 2015 International Conference on Advanced Computational Intelligence,Wuyi, 2015
  • Chair of the Program Committee for the 2013 IEEE International Conference on Grey Systems and Intelligent Services,Macau, 2013
  • Co-chair of the special session on grey systems at the 2014 IEEE International Conference on Systems, Man and Cybernetics, San Diego, 2014
  • Co-chair of the special session on grey systems at the 2012 IEEE International Conference on Systems, Man and Cybernetics, Seoul, 2012
  • Co-chair of the special session on grey systems at the 2011 IEEE International Conference on Systems, Man and Cybernetics, Anchorage, 2011
  • Co-chair of the Program Committee for the 2011 IEEE International Conference on Grey Systems and IntelligentServices, Nanjing, 2011
  • Co-chair of the Program Committee for the 2009 IEEE International Conference on Grey Systems and Intelligent Services, Nanjing, 2009
  • Session chair for 3 regular sessions at the 2008 IEEE World Congress of Computational Intelligence, Hong Kong,2008
  • Co-chair of the special session on grey systems at the 2008 IEEE World Congress of Computational Intelligence,Hong Kong, 2008
  • Member of the organising committee of the 2007 IEEE International Conference on Grey Systems and Intelligent Services, Nanjing, 2007

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