More

Professor Yingjie Yang

Job: Professor of Computational Intelligence

Faculty: Computing, Engineering and Media

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: https://www.dmu.ac.uk/cci

 

Close all sections
Open all sections

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.

Research group affiliations

Centre for Computational Intelligence (CCI) 

De Montfort University Interdisciplinary Group in Intelligent Transport Systems (DIGITS)

Publications and outputs

  • A novel grey Verhulst model with four parameters and its application to forecast the carbon dioxide emissions in China
    dc.title: A novel grey Verhulst model with four parameters and its application to forecast the carbon dioxide emissions in China dc.contributor.author: Zeng, Bo; Zheng, Tingting; Yang, Yingjie; Wang, Jianzhou dc.description.abstract: In the context of dual carbon targets, a reliable prediction of China’s carbon dioxide emissions is of great significance to the design and formulation of emission reduction policies by Chinese government. To this end, a novel grey Verhulst model with four parameters is proposed in this paper according to the evolution law and the data characteristics of China’s carbon dioxide emissions. The new model solves the defect of poor structural adaptability of the traditional grey Verhulst model by introducing a nonlinear correction term. Besides, the range of values for the order of the grey generation operator of the new model is expanded from a positive real number to any real number (r∈R+→r∈R) by expanding the value range of the Gamma function. The new model is used to simulate China’s carbon dioxide emissions, and its comprehensive mean relative percentage error is only 0.65%, which is better than that of the other three grey models (2.39%, 2.34%, 2.35% respectively). It shows that the proposed new model has better modeling ability. Finally, the new model is applied to predict China’s carbon dioxide emissions, and the results show that it will still increase year by year, reaching 13687 million tons by 2028 (only 11420 million tons in 2021). Therefore, some countermeasures and suggestions are proposed to control China’s carbon dioxide emissions in this paper. dc.description: 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.
  • Stability of Time Series Models based on Fractional Order Weakening Buffer Operators
    dc.title: Stability of Time Series Models based on Fractional Order Weakening Buffer Operators dc.contributor.author: Li, Chong; Yang, Yingjie; Zhu, Xinping dc.description.abstract: Different weakening butter operators in time series model analysis usually result in different model sensitivity, which sometimes affects the effectiveness of relevant operator-based methods. In this paper, the stability of two classic weakening buffer operator-based series models is studied; then a new data preprocessing method based on a novel fractional bidirectional weakening buffer operator is provided, whose effect in improving model stability is tested and utilized in prediction problems. Practical examples are employed to demonstrate the efficiency of the proposed method in improving model stability in noise scenarios. The comparison indicates that the proposed method overcomes the disadvantage of many weakening buffer operators in too subjectively biased weighting the new or the old information in forecasting. These expand the application of the proposed method in time series analysis dc.description: open access article
  • Grey relational analysis model with cross-sequences and its application in evaluating air quality index
    dc.title: Grey relational analysis model with cross-sequences and its application in evaluating air quality index dc.contributor.author: Lu, Ningning; Liu, Sifeng; Du, Junliang; Fang, Zhigeng; Dong, Wenjie; Tao, Liangyan; Yang, Yingjie dc.description.abstract: It is important to detect the internal operating regularity in system developing with poor information. To identify the real relationship among multi factors, we propose a grey relational analysis (GRA) method inspired by the characteristics of sequences variation. The proposed model considers the changes of fluctuating sequences like cross-sequences both in domain time and between time intervals. To obtain the quantitative change about sequences, relative angle change is employed to determine the variation in each interval, and the relative angle oscillation change is utilized for measuring variations between intervals. To find the optimal time lag or time intervals, the corresponding cycles are extracted by time-delay models. The reliability of the proposed models will be verified through cases in identifying crucial factors for air quality, and the final detection will then be made. To compare with existing representative GRA models clearly, the relation between two fluctuating sequences shaped in cross-sequences is examined by the proposed model. The empirical results show that the relation degree between pollutants and air quality is reasonable. The compared experiment shows that the GRA for cross-sequences can effectively identify the relationship among fluctuating sequences and the impact of time-delay is small for the proposed model with similar shapes. dc.description: 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.
  • MUTRISS: A new method for material selection problems using MUltiple-TRIangles scenarios
    dc.title: MUTRISS: A new method for material selection problems using MUltiple-TRIangles scenarios dc.contributor.author: Chatterjee, Prasenjit; Cheikhrouhou, Naoufei; Konstantas, Dimitri; Yang, Yingjie; Zakeri, Shervin dc.description.abstract: This paper proposes a new Multiple-criteria decision-making (MCDM) method called MUltiple-TRIangles ScenarioS (MUTRISS) with two scenarios respecting different levels of access to complete information for material selection problems. MUTRISS calculates the areas occupied by alternatives in n-dimensional space, employing analytic geometry and converting each alternative into n-edges forms. The paper applies MUTRISS to three material selection case studies, with Ti-6Al-4V, Material 4, and AISI 4140 Steel- UNS G41400 emerging as the best materials for the three examples with the highest overall scores of 0.036, 4.540 and 0.427 respectively. The results are compared with various MCDM methods through four statistical measures, including relative closeness ratio, robustness analysis, compromise ranking coefficient, and similarity degree. The measures focus on different aspects of MCDM methods in solving problems and their results. The paper concludes that MUTRISS offers a more robust and reliable approach for material selection problems compared to other MCDM methods, with the first scenario of MUTRISS being more reliable than the second scenario. The paper also emphasizes the importance of validating results in material selection problems due to the potential irreversible consequences of selecting the wrong material. dc.description: open access article
  • Grey systems and uncertainty modelling
    dc.title: Grey systems and uncertainty modelling dc.contributor.author: Yang, Yingjie; Khuman, A. S.; Liu, Sifeng dc.description.abstract: Information can, and often is, rather uncertain; with only partial information initially being made available, from which one would be able to hopefully provide for a solution. The information itself may contain conflicts that have arisen from the possible different sources used to acquire it. In addition, the information may be viewed and interpreted differently by different cohorts, this in itself can be the cause of extenuating circumstances. These are just some of the issues that one can face with uncertain information. These issues can understandably create problems when considering the deployment of applications. Being able to cater for the volatility that is inherently present in uncertainty, becomes an objective with high importance and precedence.
  • Agent-based modelling in grey economic systems
    dc.title: Agent-based modelling in grey economic systems dc.contributor.author: Delcea, Camelia; Yang, Yingjie; Liu, Sifeng; Cotfas, Liviu-Adrian dc.description.abstract: The economic systems are basically grey systems due to their components and to their interactions which enable the occurrence of uncertainty. First, the human component plays an important role as a consequence of its usually unpredictable and sometimes irrational behavior, a situation strictly related to the way the humans are thinking and acting. From here, it can easily be demonstrated that when analyzing a system, we are facing grey knowledge. This kind of knowledge exists and it represents that small piece of puzzle needed to successfully fill the gap separating the explicit knowledge form the tacit one, also conducting to uncertainty.
  • Designing optimal proactive replacement strategies for degraded systems subject to two types of external shocks
    dc.title: Designing optimal proactive replacement strategies for degraded systems subject to two types of external shocks dc.contributor.author: Dong, Wenjie; Yang, Yingjie; Cao, Yingsai; Zhang, Jingru; Liu, Sifeng dc.description.abstract: This paper mainly investigates a proactive replacement policy for a stochastically deteriorating system concurrently subject to two types of shocks. Firstly, the closed form representation of system reliability function suffering from both a degradation process and environmental shocks is derived based on the degradation-threshold failure (DTS) modelling framework. An age- and state-dependent competing risks model with mutual dependence between the two failure processes is embedded into system reliability modelling, where two types of shocks are taken into consideration upon arrival of an external shock including a minor one and a major one. Based on which, a bivariate maintenance policy is put forward for the deteriorating system, where the system is proactively replaced before failure at a planned time, or at an appropriate number of minimal repairs, whichever takes place first. The expected long-run cost rate (ELRCR) is formulated, and optimal solutions are evaluated analytically for two special cases. Finally, an illustrative example is redesigned to validate the theoretical results, exploring the significance of two types of shocks and mutual dependence in system reliability modelling, and illustrating the potential applications in maintenance decisions in various manufacturing systems. dc.description: 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.
  • Development of grey system research
    dc.title: Development of grey system research dc.contributor.author: Yang, Yingjie; Liu, Sifeng dc.description.abstract: The first chapter presents an introduction to grey system theory. We begin with some background information on the appearance and growth of grey system theory and founder “Professor Julong Deng”, who established the new branch of science. Then we examine the development history and current state, followed by a comparison of grey system theory with other uncertain systems theories such as probability and statistics, fuzzy mathematics, and rough set theory. Finally, the elementary concepts, the fundamental principles and the framework of grey system theory are presented. This introductory chapter vividly presents the reader with an overall picture of grey system theory and its frontier research.
  • End-to-end handwritten Chinese paragraph text recognition using residual attention networks
    dc.title: End-to-end handwritten Chinese paragraph text recognition using residual attention networks dc.contributor.author: Wang, Yintong; Yang, Yingjie; Chen, Haiyan; Zheng, Hao; Chang, Heyou dc.description.abstract: Handwritten Chinese recognition which involves variant writing style, thousands of character categories and monotonous data mark process is a long term focus in the field of pattern recognition research. The existing methods are facing huge challenges including the complex structure of character/line-touching, the discriminate ability of similar characters and the labeling of training datasets. To deal with these challenges, an end-to-end residual attention handwritten Chinese paragraph text recognition method is proposed, which uses fully convolutional neural networks as the main structure of feature extraction and employs connectionist temporal classification as a loss function. The novel residual attention gate block is more helpful in extracting essential features and making the training of deep convolutional neural networks more effective. In addition, we introduce the operations of batch bilinear interpolation which implement the mapping of two dimension text representation to one dimension text line representation without any position information of characters or text lines, and greatly reduce the labeling workload in preparing training datasets. In experimental, the proposed method is verified with two widely adopted handwritten Chinese text datasets, and achieves competitive results to the current state-of-the-art methods. Without using any position information of characters and text line, an accuracy rate of 90.53% is obtained in CASIA-HWDB test set. dc.description: open access article
  • A residual-attention offline handwritten Chinese text recognition based on fully convolutional neural networks
    dc.title: A residual-attention offline handwritten Chinese text recognition based on fully convolutional neural networks dc.contributor.author: Wang, Yintong; Yang, Yingjie; Ding, Weiping; Li, Shuo dc.description.abstract: Offline handwritten Chinese text recognition is one of the most challenging tasks in that it involves various writing styles, complex character-touching, and large number of character categories. In this paper, we propose a residual-attention offline handwritten Chinese text recognition based on fully convolutional neural networks, which is segmentation-free handwritten recognition that avoids the impact of incorrect character segmentation. By designing a smart residual attention gate block, our model can help to extract important features, and effectively implement the training of deep convolutional neural networks. Furthermore, we deploy an expansion factor to indicate the trade-off between computing resources for model training and the ability of a gradient to propagate across multiple layers, and make our model training adapt to different computing platforms. Experiments on the CASIA-HWDB and ICDAR-2013 competition dataset show that our method achieves a competitive performance on offline handwritten Chinese text recognition. On the CASIA-HWDB test set, the character-level accurate rate and correct rate achieve 97.32% and 97.90% respectively dc.description: open access article

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