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Professor Francisco Chiclana

Job: Professor of Computational Intelligence and Decision Making

Faculty: Technology

School/department: School of Computer Science and Informatics

Research group(s): Center for Computational Intelligence (CCI)

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

T: +44 (0)116 207 8413

E: chiclana@dmu.ac.uk

W: http://www.tech.dmu.ac.uk/~chiclana/

 

Personal profile

Professor Francisco Chiclana received the B.Sc. and Ph.D. degrees in Mathematics, both from the University of Granada (Spain) in 1989 and 2000, respectively. He is currently a Professor of Computational Intelligence and Decision Making, and founder of DIGITS - De Montfort University Interdisciplinary Group in Intelligent Transport Systems, Faculty of Technology, De Montfort University (Leicester, UK). 

Professor Francisco Chiclana was the Coordinator of DMU submission for REF 2014 UOA 11: Computer Science and Informatics. 

Professor Chiclana has been Deputy Course Leader of the MScs in Computing, Information Technology, and Information Systems Management; Programme Tutor Years 1 and 2 of the BSc/HND/FD Business Information Technology. In 2013, Professor Chiclana co-developed the Doctoral Training Programme (DTP) in Intelligent Systems (IS) that he presently co-leads. Currently, he is Course Leader of BSc/MCOMP in Intelligent Systems (IS) and of MSc IS/ IS & Robotics (ISR).

Research group affiliations

Publications and outputs 

  • Fuzzy convolutional deep-learning model to estimate the operational risk capital using multi-source risk events
    Fuzzy convolutional deep-learning model to estimate the operational risk capital using multi-source risk events Peña, Alejandro; Patiño, Alejandro; Chiclana, Francisco; Caraffini, Fabio; Gongora, Mario Augusto; Gonzalez-Ruiz, Juan David; Eduardo, Duque-Grisales Operational Risk (OR) is usually caused by losses due to human errors, inadequate or defective internal processes, system failures or external events that affect an organization. According to the Basel II agreement, OR is defined by seven risk events: internal fraud, external fraud, labour relations, clients, damage to fixed assets, technological failures and failures in the execution & administration of processes. However, due to the large amount of qualitative information, the uncertainty and the low frequency at which these risk events are generated in an organization, their modeling is still a technological challenge. This paper takes up this challenge and presents a fuzzy convolutional deep-learning model to estimate, based on the Basel III recommendations, the ORLoss Component(OR-LC) in an organization. The proposed model integrates qualitative information as linguistic random variables, as well as risk events data from different sources using multi-dimensional fuzzy credibility concepts. The results show the stability of the proposed model with respect to the OR-LC estimation from both structural and dimensional point of views, making it an ideal tool for modeling OR from the perspective of: (a) the regulators (Basel Committee on Banking Supervision) by allowing the integration of experts’ criteria into the OR-LC; (b) the insurers by allowing the integration of risk events from different sources; and (c) organizations and financial entities by allowing the a priori evaluation of the OR-LC of new financial products based on technological platforms and electronic channels.
  • A dynamic feedback mechanism with attitudinal consensus threshold for minimum adjustment cost in group decision making
    A dynamic feedback mechanism with attitudinal consensus threshold for minimum adjustment cost in group decision making Sun, Qi; Wu, Jian; Chiclana, Francisco; Fujita, Hamido; Herrera-Viedma, Enrique This article presents a theoretical framework for a dynamic feedback mechanism in group decision making (GDM) by the implementation of an attitudinal consensus threshold (ACT) to generate recommendation advice for the identified inconsistent experts with the aim to increase consensus. The novelty of the approach resides in its ability to implement the ACT continuously, which allows the covering of all possible consensus states of the group from its minimum to maximum consensus degrees. Therefore, it can be flexibly applied to GDM problems with different consistency requirements. A sensitivity analysis method with visual simulation is proposed to support the checking of the numbers of experts involved in the feedback process and the minimum adjustment cost associated with the different ACT intervals. Experimental results show that an increase in the ACT value will lead to an increase in the number of experts and adjustment cost involved in the feedback process. Eventually, a numerical example is included to simulate the feedback process under various decision making scenarios with different ACT intervals. 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.
  • Bounded Confidence Evolution of Opinions and Actions in Social Networks
    Bounded Confidence Evolution of Opinions and Actions in Social Networks Zhan, Min; Kou, Gang; Dong, Yucheng; Chiclana, Francisco; Herrera-Viedma, Enrique Inspired by the continuous opinion and discrete action model, bounded confidence and social networks, the bounded confidence evolution of opinions and actions in social networks is investigated and a social network opinions and actions evolutions (SNOAE) model is proposed. In the SNOAE model, it is assumed that each agent has a continuous opinion and discrete action for a certain issue. Agents’ opinions are private and invisible, i.e. an individual agent only knows their own opinion and cannot obtain other agents’ opinions unless there is a social network connection edge that allows their communication; agents’ actions are public and visible to all agents and impact on other agents’ actions; and opinions and actions evolve in a directed social network. In the limitation of the bounded confidence, other agents’ actions or agents’ opinions noticed or obtained by network communication, respectively, are used by agents to update their opinions upon. Based on the SNOAE model, the evolution of the opinions and actions with bounded confidence is investigated in social networks both theoretically and experimentally with a detailed simulation analysis. Theoretical research results show that discrete actions can attract agents who trust the discrete action, and make agents to express extreme opinions. Simulation experiments results show that social network connection probability, bounded confidence, and the opinion threshold of action choice parameters have strong impacts on the evolution of opinions and actions. However, the number of agents in the social network has no obvious influence on the evolution of opinions and actions. 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 family of similarity measures for q‐rung orthopair fuzzy sets and their applications to multiple criteria decision making
    A family of similarity measures for q‐rung orthopair fuzzy sets and their applications to multiple criteria decision making Farhadinia, Bahram; Effati, Sohrab; Chiclana, Francisco One worthwhile way of expressing imprecise information is the q‐rung orthopair fuzzy sets (q‐ROFSs), which extend intuitionistic fuzzy sets and Pythagorean fuzzy sets. The main goal of this contribution is to further extend the concept of similarity measure for q‐ROFSs, which not only endows the similarity framework with more ability to create new ones but also inherits all essential properties of a logical similarity measure. This contribution proposes a class of novel similarity measures for q‐ROFSs by drawing a general framework of existing q‐ROFS similarity and q‐ROFS distance measures. These q‐ROFS similarity measures enable us to overcome the theoretical drawbacks of the existing measures in the case where they are used individually. In the application part of the contribution, a pattern recognition problem on classification of building materials with a number of known building materials is reconsidered. The study of this particular case shows that the proposed family of similarity measures consistently classify the unknown building material pattern with the same known building material pattern. Then, an experimental case study regarding a problem of classroom teaching quality is re‐examined for the comparison of the performance of proposed similarity measures against the existing ones. The salient features of the proposed similarity measures in comparison to the existing qROFS similarity measures, are as follows: (i) a number of existing q‐ROFS similarity measures are inherently correlation coefficients, and they satisfy only a limited number of essential properties of a comprehensive similarity measure; (ii) several existing q‐ROFS similarity measures lead sometimes to nonlogical results, more specifically, to the same maximum similarity value for different q‐ROFSs; (iii) a variety of existing q‐ROFS similarity measures depend on subjective parameters, which either hinder their application in practice or increase their computational cost. In brief, following this direction of research, we will prove the superiority of the developed similarity measures over the existing ones from both theoretical and experimental viewpoints. 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 decision making methodology based on the weighted correlation coefficient in weighted extended hesitant fuzzy environments
    A decision making methodology based on the weighted correlation coefficient in weighted extended hesitant fuzzy environments Farhadinia, Bahram; Chiclana, Francisco Correlation is an important index in decision-making. In weighted extended hesitant fuzzy sets (WEHFSs) environment, researchers have only defined a class of correlation coefficients between WEHFSs with values in the unit interval [0, 1]. This is not ideal because it does not extend the classical correlation coefficient in the case of classical sets. In fact, the negative values of the interval [−1, 1] are ignored, and such a neglectfulness leads to unreasonable results in decision making. In other words, the existing definitions are unconvincing and lack consistency, which hinder their application potentials. This article addresses this issue by introducing a new class of weighted correlation coefficients of WEHFSs with values in the interval [−1, 1]. Three decision making methodologies based on the weighted correlation coefficients of WEHFSs are compared with the existing methodologies based on their respective correlation coefficients in the unit interval [0, 1]. The comparative analysis shows both the efficiency and effectiveness of the new correlation index. 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.
  • Consensus and opinion evolution-based failure mode and effect analysis approach for reliability management in social network and uncertainty contexts
    Consensus and opinion evolution-based failure mode and effect analysis approach for reliability management in social network and uncertainty contexts Zhang, Hengjie; Dong, Yucheng; Xiao, Jing; Chiclana, Francisco; Herrera-Viedma, Enrique As a forward-looking reliability-management engineering technique, failure mode and effect analysis (FMEA) has been widely utilized to improve the reliability of products, processes, systems, and services. In practice, multiple responsible parties for FMEA implementation have different backgrounds, knowledge levels, and opinions. Integrating consensus into FMEA has some notable merits: the connections between FMEA participants can be strengthened, and a collective solution with a high degree of acceptability to the FMEA problem can be yielded. Meanwhile, the social network relationship among FMEA participants should be an essential element in FMEA because the participants’ opinions are subject to influence by each other and likely to evolve due to their social network interactions. Thus, this study first proposes a social network consensus model with minimum adjustment distance to assist FMEA participants in attaining a consensus, in which participants utilize a linguistic distribution assessment approach to represent their opinions. Second, an opinion evolution-based social network consensus model with minimum adjustment distance is further presented by considering the phenomenon of opinion evolution. Finally, some theoretical analyses, a case study, and a detailed comparative analysis are presented to verify the validity of the proposed FMEA approach. 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.
  • Revisiting Fuzzy and Linguistic Decision-Making: Scenarios and Challenges for Wiser Decisions in a Better Way
    Revisiting Fuzzy and Linguistic Decision-Making: Scenarios and Challenges for Wiser Decisions in a Better Way Herrera-Viedma, Enrique; Palomares, Ivan; Li, Cong-Cong; Cabrerizo, Francisco Javier; Dong, Yucheng; Chiclana, Francisco; Herrera, Francisco This paper provides a brief tour through the main fuzzy and linguistic decision-making trends, studies, methodologies and models developed in the last 50 years. Fuzzy and linguistic decision-making approaches allow to address complex real-world decision problems where humans exhibit vagueness, imprecision and/or use natural language to assess decision alternatives, criteria, etc. The aim of this paper is threefold. Firstly, the main fuzzy set theory and computing with words based representation paradigms of decision information, with their different levels of expressive richness and complexity, are reviewed. Secondly, three core decision-making frameworks are examined: (1) multi-criteria decision-making, (2) group consensus-driven decision-making, and (3) multi-person multi-criteria decision making. Thirdly, the paper discusses new complex decision making frameworks that have emerged in recent years, where decisions are guided by the “wisdom of the crowd”: their associated challenges are highlighted and considerations on much needed key guidelines for future research in the field are provided. 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 knowledge coverage-based trust propagation for recommendation mechanism in social network group decision making
    A knowledge coverage-based trust propagation for recommendation mechanism in social network group decision making Liu, Yujia; Liang, Changyong; Chiclana, Francisco; Wu, Jian Trust is a typical relationship in social network, which in group decision making problems relates to the inner relationship among experts. To obtain a complete trust relationship of a networked group of experts, firstly, a novel knowledge coverage-based trust propagation operator is proposed to estimate the trust relationship between pairs of unknown experts. The novelty of this trust propagation operator resides in its account of the domain knowledge coverage of experts. Desirable properties regarding boundary conditions, generalisation and knowledge coverage absorption are studied. The comparison with existing operators of boundary conditions shows the rationality of the proposed operator. Next, a knowledge coverage-based multi-paths trust propagation model for constructing complete trust network is investigated. The proposed approach aggregates all trust paths to collect all trust information and penalise trust decay. Secondly, a trust order induced recommendation mechanism is proposed by combining subjective and objective weights. Thus, experts can accept consensus recommendations by subjective and objective trust. This recommendation mechanism allows the inconsistent experts to accept the advices they trust. The validity and rationality of the proposed recommendation mechanism is mathematically proved, and a numerical example is utilised to illustrate the calculation process of the proposed method. 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.
  • The Stratic Defuzzifier for Discretised General Type-2 Fuzzy Sets
    The Stratic Defuzzifier for Discretised General Type-2 Fuzzy Sets Greenfield, Sarah; Chiclana, Francisco Stratification is a feature of the type-reduced set of the general type-2 fuzzy set, from which a new technique for general type-2 defuzzification, Stratic Defuzzification, may be derived. Existing defuzzification strategies are summarised. The stratified structure is described, after which the Stratic Defuzzifier is presented and contrasted experimentally for accuracy and efficiency with both the Exhaustive Method of Defuzzification (to benchmark accuracy) and the alpha-Planes/Karnik–Mendel Iterative Procedure strategy, employing 5, 11, 21, 51 and 101 alpha-planes. The Stratic Defuzzifier is shown to be much faster than the Exhaustive Defuzzifier. In fact the Stratic Defuzzifier and the alpha-Planes/Karnik–Mendel Iterative Procedure Method are comparably speedy; the speed of execution correlates with the number of planes participating in the defuzzification process. The accuracy of the Stratic Defuzzifier is shown to be excellent. It is demonstrated to be more accurate than the alpha-Planes/Karnik–Mendel Iterative Procedure Method in four of six test cases, regardless of the number of -planes employed. In one test case, it is less accurate than the alpha-Planes/Karnik–Mendel Iterative Procedure Method, regardless of the number of alpha-planes employed. In the remaining test case, the alpha-Planes/Karnik–Mendel Iterative Procedure Method with 11 alpha-Planes gives the most accurate result, with the Stratic Defuzzifier coming second. 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.
  • Performance of Execution Tracing with Aspect-Oriented and Conventional Approaches
    Performance of Execution Tracing with Aspect-Oriented and Conventional Approaches Galli, Tamas; Chiclana, Francisco; Siewe, Francois Context: Most software product quality models contain a quality property to describe the performance of the software products under assessment. In addition, software product quality models exhibit a quality property to describe how maintainable the investigated software product is. These two quality properties are conflicting as good maintainability values require that the amount of information about the threads of execution in the application, method stacks including parameters, return values and changes of the internal states be available. Collecting and storing this amount of information in a trace output takes time and consumes resources, which deteriorates execution performance. The major expectation towards the trace data is accuracy and consistency and, as a second priority, to achieve an acceptable performance degradation. Aspect-oriented programming offers assistance to satisfy these goals, however the published data about the aspect-oriented performance are not up to-date; moreover, they do not measure the performance of execution tracing but the performance of aspect-oriented programming constructs. Objectives: We aim to measure the performance of execution tracing with a simple but very resource intensive test application pair implementing the same functionality, producing the same amount of trace data. The one application possesses aspect-oriented execution tracing while the other one conventional, object-oriented execution-tracing with manually inserted trace method calls. In addition, we plan to separately measure the performance impact of constructing the trace messages by collecting the data in the applications; moreover, the performance impact of writing these data into a physical file is also measured. Method: We introduce a true experimental research with full control over the research variables to measure the runtimes of two very resource intensive test applications with exactly the same functionality, one with conventional tracing where the trace method calls were manually inserted at the entry and exit points of each method and the other one where the trace method calls were inserted by aspect-oriented programming with compile-time weaving automatically. We have selected such a pressing tracing policy to study the differences at maximal margin. In addition, no logging frameworks were used to rule out their performance effects. Both test applications produce the same bytes of trace data between the points of time measurements. Moreover, the two test applications were run in parallel, in three ways: (1) with deactivated tracing, (2) with activated tracing with output in /dev/null, (3) with activated tracing with output in a real file, to eliminate the impact of extraneous variables while computing runtime ratios of conventional and aspect-oriented execution tracing. As platform we have chosen Java and AspectJ in version 1.8 and 1.9, which at the time of writing the manuscript is the latest available AspectJ version, to examine whether Java and aspectJ versions have an impact on the performance of execution tracing. Results: The measurements produced results with very strong statistical significance (p < 0.001): (1) different Java and AspectJ versions have different performance impacts on execution tracing, (2) constructing the trace messages in the two test applications had more impact on the performance than writing these data in real files, (3) aspect-oriented implementation of execution tracing deteriorated the performance with deactivated tracing compared to the non-aspect-oriented implementation, (4) the aspect-oriented implementation of execution tracing produced only an acceptable performance overhead with activated tracing compared to the non-aspect-oriented counterpart with activated tracing. Measurement data are provided in the appendix.


Click here to view a full listing of Francisco Chiclana's publications and outputs.

Key research outputs

F. Chiclana, E. Herrera-Viedma, S. Alonso, F. Herrera: Cardinal Consistency of Reciprocal Preference Relations: A Characterization of Multiplicative Transitivity. IEEE Transactions on Fuzzy Systems 17 (1), 14-23, February 2009. doi:10.1109/TFUZZ.2008.928597

S. -M. Zhou, F. Chiclana, R. I. John, J. M. Garibaldi: Type-1 OWA Operators for Aggregating Uncertain Information with Uncertain Weights Induced by Type-2 Linguistic Quantifiers. Fuzzy Sets and Systems 159 (24), 3281-3296, December 2008. doi:10.1016/j.fss.2008.06.018 

S-M. Zhou, F. Chiclana,R. John, J. M. Garibaldi: Alpha-Level Aggregation: A Practical Approach to Type-1 OWA Operation for Aggregating Uncertain Information with Applications to Breast Cancer Treatments. IEEE Transactions on Knowledge and Data Engineering 23 (10) 1455-1468, October 2011. doi: 10.1109/TKDE.2010.191

F. Herrera, E. Herrera-Viedma, S. Alonso, F. Chiclana: Computing with Words in Decision Making: Foundations, Trends and Prospects. Fuzzy Optimization and Decision Making 8, 337-364, 2009 (ISSN: 1568-4539). doi: 10.1007/s10700-009-9065-2

Patrizia Pérez-Asurmendi, F. Chiclana: Linguistic majorities with difference in support. Applied Soft Computing 18, May 2014, Pages 196–208. doi: 10.1016/j.asoc.2014.01.010

F. Chiclana, J. M. Tapia-Garcia, M. J. del Moral, E. Herrera-Viedma: A Statistical Comparative Study of Different Similarity Measures of Consensus in Group Decision Making. Information Sciences 221, 110-123, February 2013, doi: 10.1016/j.ins.2012.09.014

Jian Wu, F. Chiclana: A social network analysis trust-consensus based approach to group decision-making problems with interval-valued fuzzy reciprocal preference relations. Knowledge-Based Systems 59, March 2014, Pages 97–107. doi: 10.1016/j.knosys.2014.01.017

S. Greenfield, F. Chiclana, S. Coupland, R. I. John: The Collapsing Method of Defuzzification for Discretised Interval Type-2 Fuzzy Sets. Information Sciences 179(13), 2055-2069, June 2009. doi: 10.1016/j.ins.2008.07.011

S. Greenfield, F. Chiclana, R. John, S. Coupland: The Sampling Method of Defuzzification for Type-2 Fuzzy Sets: Experimental Evaluation. Information Sciences 189, 77-92, April 2012. doi: 10.1016/j.ins.2011.11.042

E. Herrera-Viedma, F. Herrera, F. Chiclana , M. Luque: Some Issues on Consistency of Fuzzy Preference Relations. European Journal of Operational Research 154(1), 98-109, April 2004. doi:10.1016/S0377-2217(02)00725-7

F. Chiclana, F. Herrera, E. Herrera-Viedma: Integrating Three Representation Models in Fuzzy Multipurpose Decision Making Based on Fuzzy Preference Relations. Fuzzy Sets and Systems 97(1), 33-48, July 1998. doi:10.1016/S0165-0114(96)00339-9 

Research interests/expertise

Fuzzy preference modelling, decision making problems with heterogeneous fuzzy information, decision support systems, the consensus reaching process, recommender systems, social networks, modelling situations with missing/incomplete information, rationality/consistency, intelligent mobility and aggregation of information. 

Areas of teaching

I have a lot of teaching experience that I have acquired over the past 21 years as a secondary school teacher of mathematics (Granada, Montoro-Cordoba, Estepona and Mabella - Malaga) in Spain (September 1990 - July 2003), and at De Montfort University (August 2003 - present) lecturing different modules at undergraduate, postgraduate (MSc) and PhD levels (see list below). Previously, I worked as a temporary lecturer at the Department of Algebra, University of Granada, in Spain (January 1990-March 1990) teaching calculus and financial mathematics to first year students of management studies.

In June 2005, I completed the HEA accredited programme for staff new to teaching in Higher Education which entitled me to registered practitioner status of the Higher Education Academy. Certificate presentation was on 28th September 2005 by the Director of Human Resources. I was glad to have Dr Jenny Carter as my mentor during my first 2 years at DMU. Currently, I am a fellow of the Higher Education Academy.

I was nominated by students for a Vice-Chancellor's Distinguished Teaching Award in 2009. The students think highly of me and my contribution to the student experience is valued as the following quotation testifies:

"He willingly devotes time to listen to any student and has helped me to achieve good mark. He is consistently excellent communicator, stimulating and informative..."         

 

Areas of Teaching:
  • Mathematics for Computing
  • Financial Mathematics
  • Statistics
  • Research Methods
  • Fuzzy Logic

 

Qualifications

  • Certificate Successful completion of HEA accredited pathway for staff new to teaching in Higher Education, De Montfort University, Leicester, UK (September 2005)
  • Outstanding Award for a PhD in Mathematics for the academic year 1999/2000, University of Granada, Spain (27 November 2002)
  • PhD in Mathematics (Distinction Cum Laude), Department of Computer Science and Artificial Intelligence, University of Granada, Spain (24 March 2000)
  • Public examination to become part of government civil service as a secondary school teacher, Ministry of Education and Science, Spanish Government (July 1990)
  • Degree in Mathematics (Statistics & Operational Research), University of Granada, Spain (1984-1989)
  • Certificate of Pedagogic Aptitude, Institute of Educational Science, University of Granada, Spain (1989).

Courses taught

Undergraduate

CSCI1004 - Mathematics for Computing (2003-2004)
MGSC1102 - Modelling for Management Decisions 1 (2003-2004)
INFO1007 - Introduction to Business Computing (2003-2004)
INFO1407 - Introduction to Business Computing (2004-2007)
MATH2211 - Information Systems (2003-2005)
COMP2006 - Research in Computing (2004-2008)
CSCI1412 - Computer Technology (2007-2010)
Industrial Placement Visit Tutor (2003-2012)
IMAT1901: Quantitative Methods (2010-2012)
IMAT2701: HND BIT Project (2009-2012)
IMAT3451 - Final Year Project Supervisor (2003-2012)

Postgraduate

IMAT5119 - Fuzzy Logic (2004-2012)
IMAT5120 - Research Methods (2004-2012)
IMAT5314 - MSc Project (2010-2012)

PhD Level

PhD Course: Typesetting Documents with LaTeX (2004-2012)  

Honours and awards

Outstanding Award for a PhD in Mathematics for the academic year 1999/2000, University of Granada, Spain (27 November 2002).

Third prize in DMU’s Creative Thinking Awards 2010, for the Greenfield-Chiclana Collapsing Defuzzifier.

Finalist for 1st DMU - THE OSCAR AWARDS  in category: Outstanding Contribution to Research Excellence (2012).

Membership of external committees

Fellow of the Higher Education Academy, UK

Member of the European Society for Fuzzy Logic and Technology (EUSFLAT) 

Current research students

Current:

  • Maria Raquel Ureña Perez, University of Granada (Spain)- Department of Computer Science and Artificial Intelligence (DECSAI), University of Granada. January 2012. Co-supervisor: Prof. Enrique Herrera-Viedma
  • Manal Alghieth (DMU) - Second supervisor. First supervisor: Dr Yingjie Yang (CCI). Mode of study: Full -time on site (01/04/2012)
  • Simon Witheridge (DMU) - Intelligent Transport Systems: Integrated Traffic Management Control. First supervisor. Second supervisors: Dr Benjamin Passow (DIGITS) and Dr David Elizondo (DIGITS). Mode of study: Full -time on site (01/10/2012). Change to second supervisor and Ben Passow first supervisor from 01-October-2013.
  • Eseosa Oshodin (DMU) - Decentralised Mechanism for REcommender/Reputation System: A Case Study on Trust. First supervisor. Second supervisors: Dr Samad Ahmadi (VirAL/CCI). Mode of study: Full -time on site (01/10/2013).
  • Salim Hasshu (DMU) - Smart, Green and Integrated Transport - Personalised traffic health planner. First supervisor. Second supervisors: Dr Benjamin Passow (DIGITS) and Dr David Elizondo (DIGITS). Mode of study: Full -time on site (01/10/2013).

Completed:

  • Dr Sergio Alonso Burgos, University of Granada (Spain)- Group Decision Making With Incomplete Fuzzy Preference Relations. Department of Computer Science and Artificial Intelligence (DECSAI), University of Granada. May 2006. Co-supervisors: Prof. Enrique Herrera-Viedma, Prof. Francisco Herrera.
  • Dr Fahad Alshathry (DMU) - Building a Decision Support System to integrate digital evidence with interview investigation. Second supervisor. August 2011. First supervisor: Dr Giampaolo Bella (STRL).
  • Dr Sarah Greenfield (DMU) - Type-2 Fuzzy Logic: Circumventing the Defuzzification Bottleneck. First supervisor. Second supervisors: Prof. Robert I. John and Dr Simon Coupland (CCI). May 2012.
  • Tamas Galli (MPhil DMU) - Fuzzy Logic Based Software Product Quality Models by Execution Tracing. First supervisor. Second supervisor: Dr Jenny Carter (CCI). Technical adviser: Helge Janicke (STRL). Mode of study: Part -time distance International PhD Programme (01/03/2011). February 2014.

Externally funded research grants information

  • Awarded Campus de Excelencia GENIL-BioTIC-UGR Research Visit Grant (1 week) by the University of Granada (Spain). Principal Investigator. €1000. Period: February 2014.
  • Awarded Campus de Excelencia GENIL-BioTIC-UGR Research Visit Grant (1 week) by the University of Granada (Spain). Principal Investigator. €1200. Period: June 2012.
  • Awarded University of Granada Research Visit Grant by the Regional Government of Andalucia (Spain). Principal Investigator. €3184. Period: June 2009 - August 2009.
  • Awarded research funding from the EPSRC for a 3 year projet, which extends my previous work investigating the role of fuzzy logic in aggregation and consensus modelling. Towards a Framework for Modelling Variation, EPSRC, UK, Co-investigator. £145K. Period: 2006 - 2009.
  • Awarded a Royal Academy of Engineering grant support towards my research networking visit to Spain. 2009.
  • Awarded 2 Conference Grants (Royal Society and Royal Academy of Engineering) to disseminate my research findings at IPMU 2006 and FUZZ-IEEE 2008.
  • External research collaborator in Spanish Government Research Projects lead by my collaborators.
  • Linguistic Information in Decision Making Analysis Processes. Preference Modelling and Applications. Spanish Department for Education and Culture, Co-investigator. €91K. Period: 01/01/2010 to 31/12/2012.  
  • Project of Excellence: Developing the Fuzzy Linguistic Model and its Use in WEB Applications. Regional Government of Andalucia (Spain), Co-investigator. €187K. Period: 01/01/2009 to 31/12/2013.
  • Decision Models with Uncertainty in Heterogeneous Contexts. Application to Evaluation Processes in On-line Environments. Spanish Department for Education and Culture, Co-investigator. €50K. Period: 01/01/2007 to 31/12/2009.
  • Project of Excellence: Development of WEB Information Access Systems Based on Artificial Intelligence Techniques (SAINFOWEB). Regional Government of Andalucia (Spain), Co-investigator. €50K. Period: 01/01/2005 to 31/12/2008.
  • An Information System for the Quality of Aerial Transportation Based on Artificial Intelligence Techniques and Oriented Towards the Citizen. Spanish Department of Transport, Co-investigator. €96K. Period: 01/01/2005 to 31/12/2008.
  • Flexible Preference Modelling in Decision Making. Applications in online recommender systems (I) and (II). Spanish Department for Education and Culture, Co-investigator. €33K. Period: 01/01/2003 to 31/12/2006.
  • Spanish National Network in Decision Making, Preference Modelling and Aggregation (I) and (II). Spanish Department for Education and Culture, Co-investigator. €30K. Period: 01/01/2004 to 31/12/2006.
  • Similarities Between Physics and Mathematics in Secondary Education. Regional Government of Andalucia (Spain), Principal Investigator. €700. Period: 01/09/2002 to 30/06/2003.

 

Internally funded research project information

  • Awarded DMU Research Scholarship 2013-14 scheme for 3 years starting from October 2013. This scheme provides for funding to cover both fees and stipend equivalent to the RCUK standard rate (£13,770 for 2012-13) to support one research student from UK or EU. (Principal Investigator with Dr David Elizondo and Dr Benjamin Passow - DIGITS).
  • Awarded DMU Research Scholarship 2012-13 scheme for 3 years starting from October 2012.  This scheme provides for funding to cover both fees and stipend equivalent to the RCUK standard rate (£13,770 for 2012-13) to support one research student from UK or EU. (PI with Dr David Elizondo and Dr Benjamin Passow - DIGITS).
  • Awarded DMU Revolving Investment Fund (RIF) for Research for the project DIGITS: De Montfort Interest Group In Transport Systems. Principal Investigator. £10K. Period: January 2012 - July 2012. 
  • Awarded £4K under the Faculty of Computing Sciences and Engineering (DMU) Pump Priming initiative to promote external collaborations at the University of Granada and the University of Jaen in Spain. 2005.

Professional esteem indicators

Associate Editor and Editorial Board

International journals in ISI Web of Knowledge

International journals not in ISI Web of Knowledge

Guest Editor for international journals in ISI

  • "FUZZY APPROACHES IN PREFERENCE MODELLING, DECISION MAKING AND APPLICATIONS" in the International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems (IJUFKS), Volume 16, Issue 2 Supp. August 2008. F. Chiclana, E. Herrera-Viedma, S. Alonso, F. Herrera (Eds.).
  • "COMPUTING WITH WORDS IN DECISION MAKING" in the International Journal of Fuzzy Optimization and Decision Making Journal, Volume 8, Number 4 / December 2009. F. Herrera, E. Herrera-Viedma, S. Alonso and F. Chiclana (Eds.). 

Research Council Reviewer and External Examiner

UK

  • EPSRC
  • The Royal Society

International

  • The Research Foundation - Flanders (Belgium) (Fonds Wetenschappelijk Onderzoek - Vlaanderen, FWO)
  • The Romanian National Council for Development and Innovation
  • Portuguese Foundation for Science and Technology (FCT)
  • Austrian Science Fund (FWF)
  • Netherlands Organisation for Scientific Research, Division of Social Sciences.

PhD external examiner

  • Univ. Granada (Granada, Spain)
  • Univ. Jaén (Jaén, Spain)
  • Ulster University (Belfast, UK)
  • University of Valladolid (Valladolid, Spain)
  • École Supérieure d'Électricité (SUPÉLEC, Paris, France).

Conference Organisation, Plenary Talks and Invited Lectures

Organised and Chaired special sessions in the following international conferences:  

  • Special Session FZ08: Fuzzy decision-making: Consensus and Missing Preferences in FUZZ-IEEE 2014 - Beijing (China) that will be held as part of the WCCI2014 from 6-11 July 2014.
  • Special Session 04: Fuzzy Preference Modelling, Decision Making and Consensus in the Second International Conference on Information Technology and Quantitative Management (ITQM2014) that will be held in Moscow - Russia from 3-5 June 2014.
  • Focus Session on Consensus and Decision Making Under Uncertainty in the 2013 IFSA World Congress NAFIPS Annual Meeting Edmonton, Canada June 24-28, 2013.
  • Special Session on Fuzzy Preference Modelling, Decision Making and Consensus in first International Conference of Information Technology and Quantitative Management (ITQM 2013), May 16-18, 2013 at Suzhou, China.
  • Special Session on "Fuzzy Approaches in Preference Modelling, Decision Making and Applications" for the IEEE International Conference on Fuzzy Systems (FUZZ_IEEE), London, UK (2007).
  • Special Session on "Soft Decision Making - Theory and Applications" for the IEEE International Conference on Fuzzy Systems (FUZZ_IEEE), Hong-Kong, China (2008).
  • Special Session on "Fuzzy Decision Making Issues: Preference Modelling and Aggregation" for the 8th International FLINS Conference on Computational Intelligence in Decision and Control, Madrid, Spain (2008).
  • Organised Workshop on "Type-2 Fuzzy Logic and the Modelling of Uncertainty" at the AI-2007 Twenty-seventh SGAI International Conference on Artificial Intelligence, Cambridge, UK.
  • Plenary talk at the 2009 EUROFUSE Workshop on Preference Modelling and Decision Analysis.
  • Invited Lectures at the University of Granada, the University of Pamplona, the University of Valladolid, the University of Castilla-La Mancha in Albacete, the University of Jaen (Spain), Ghent University (Belgium) and University of Portsmouth (UK).
  • Programme committee member of more than 50 international conferences.
Francisco-Chiclana

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