Publications 

Books and Edited Volumes

• Van-Nam Huynh, Yoshiteru Nakamori, Hiroakira Ono, Jonathan Lawry, Vladik Kreinovich, Hung T. Nguyen, editors. Interval/Probabilistic Uncertainty and Non-Classical Logics. Springer. 2008

• Jonathan Lawry. Modelling and Reasoning with Vague Concepts. Springer. 2006

• Jonathan Lawry, Enrique Miranda, Alberto Bugarin, Shoumei Li, Maria Angeles Gil, Przemyslaw Grzegorzewski and Olgierd Hyrniewicz, editors. Soft Methods for Integrated Uncertainty Modelling. Springer. 2006

• Miguel Lopez-Diaz, Maria A Gil, Przemyslaw Grzegorzewski, Olgierd Hyrniewicz and Jonathan Lawry, editors. Soft Methodology and Random Information Systems . Springer . 2004

• Jonathan Lawry,Jimi Shanahan and Anca Ralescu, editors. Modelling with Words ,vol. 2873. Springer . June 2003.

Journal and Conference Papers

2008

• Jonathan Lawry, Appropriateness Measures: An Uncertainty Model for Vague Concepts, Synthese, Vol. 161, No.2: 255--269, 2008

• Zengchang Qin, Jonathan Lawry, LFOIL: Linguistic Rule Induction in the Label Semantics Framework, Fuzzy Sets and Systems, Vol. 159, No. 4: 435--448, 2008

• Jonathan Lawry, Label Semantics as a Framework for Granular Modelling, in Interval/Probabilistic Uncertainty and Non-Classical Logics, Ed V-N. Huynh, Y. Nakamori, H. Ono, J. Lawry, V. Kreinovich, H. T. Nguyen: 87-102, 2008

2007

• Jim Hall, Guangtao Fu and Jonathan Lawry. Imprecise Probabilities of Climate Change: Aggregation of Fuzzy Scenarios and Model Uncertainties. Climatic Change, Vol. 81, Nos. 3-4: 265--281, 2007

• Nick Randon, Jonathan Lawry, Kevin Horsburgh, Ian Cluckie. Fuzzy Bayesian Modelling of Sea-Level along the East Coast of Britain, to appear in: IEEE Transaction on Fuzzy Systems

• Jonathan Lawry, An Overview of Computing with Words using Label Semantics  in: Fuzzy Sets and Their Extensions: Representation, Aggregation and Models, Ed. H. Bustince, F. Herrera, J. Montero, Studies in Fuzziness and Soft Computing: 65--872007

• Zengchang Qin and Jonathan Lawry.  Fuzzy label semantics for data mining, In: Forging the New Frontiers: Fuzzy Pioneers II, Ed. M. Nikravesh, J. Kacprzyk, and L. A. Zadeh, Studies in Fuzziness and Soft Computing: 269--297, Springer, 2007

• Zengchang Qin and Jonathan Lawry. Fuzziness and performance: an empirical study with linguistic decision trees,  IFSA-07 World Congress, Cancun, Mexico, 2007 (PDF)

• Van Nam Huynh, Yoshiteru Nakamori and Jonathan Lawry. A probability-based approach to comparison of fuzzy numbers and applications to target-oriented decision making, to appear in: IEEE Transactions on Fuzzy Systems, 2007

• Zengchang Qin and Jonathan Lawry. Knowledge Discovery in a Framework of Modelling with Words, in Soft Computing for Knowledge Discovery and Data Mining Ed. O. Mairmon, L. Rokoch: 241--276, 2007

• Daniel R McCulloch, Jonathan Lawry, M.A. Rico-Ramirez, I.D. Cluckie. Classification of Weather Radar Images using Linguistic Decision Trees with Conditional Labelling, in Proceedings IEEE Fuzzy Systems Conference, 2007

• Daniel R McCulloch, Jonathan Lawry, M.A. Rico-Ramirez, I.D. Cluckie. Detecting Bright Band using AI Techniques in Radar Hydrology. Proceedings International Conference on Remote Sensing, Perugia, Italy, 2007

• Jonathan Lawry, Hongmei He. Linguistic Attribute Hierarchies for Multiple-Attribute Decision Making, in Proceedings IEEE Fuzzy Systems Conference, 2007

2006

• Nick Randon and Jonathan Lawry. Classification and Query Evaluation using Modelling with Words. Information Sciences, Vol 176 :438--464

• Jonathan Lawry and Van Nam Huynh. A Possible Worlds Interpretation of Labels Semantics, In: Information Processing and Management of Uncertainty (IPMU 06), July 2006. (PDF)

• Van Nam Huynh, Yoshiteru Nakamori and Jonathan Lawry. Ranking Fuzzy Numbers using Targets, In: Information Processing and Management of Uncertainty (IPMU 06), July 2006.

• Olliver Turnbull, Arthur Richards, Jonathan Lawry, and Mark Lowenburg. Fuzzy Decision Tree Cloning of Flight Trajectory Optimisation for Rapid Path Planning, in: 45 IEEE Conference on Decision and Control, December 2006

• Nick Randon and Jonathan Lawry, Online Learning for Fuzzy Bayesian Prediction, in Soft Methods for Integrated Uncertainty Modelling, Springer

2005

• Jonathan Lawry, G. Fu and J. W. Hall. A Granular Semantics for Fuzzy Measures and its Applications to Climate Change Scenarios. In: 4th International Symposium on Imprecise Probabilities and Their Applications, July 2005. (PDF)

• Zengchang Qin and Jonathan Lawry. Hybrid Bayesian estimation trees based on label semantics. In: Eighth European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, pages 896--907. Springer , July 2005.

• Zengchang Qin and Jonathan Lawry. Linguistic rule induction based on a random set semantics. In: World Congress of International Fuzzy Systems Association (IFSA-05), July 2005. (PDF)

• Zengchang Qin and Jonathan Lawry. Prediction trees using linguistic modelling. In: World Congress of International Fuzzy Systems Association (IFSA-05), July 2005. (PDF)

• Zengchang Qin and Jonathan Lawry. Decision Tree Learning with Fuzzy Labels. Information Sciences, vol. 172: 91--129, June 2005.

2004

• Jonathan Lawry, Dawei Han and Ian Cluckie. Fuzzy Rule Generation in Hydrological Modelling. In: Soft Methodology and Random Information Systems, pages 741--748. Springer, September 2004. 

• Zengchang Qin and Jonathan Lawry. ROC Analysis of a Linguistic Decision Tree Merging Algorithm. In: 2004 UK Computational Intelligence, pages 33--42. September 2004. (PDF)

• Zengchang Qin and Jonathan Lawry. A Tree-Structured Classification Model Based on Label Semantic. In: Information Processing and Management of Uncertainty (IPMU 04), July 2004.

• Jim W Hall and Jonathan Lawry. Generation, combination and extension of random set approximations to coherent lower and upper probabilities. Reliability Engineering and Systems Safety ,volume 85(1-3): 89--101, July 2004.

• Nick Randon, Jonathan Lawry, Dawei Han and Ian Cluckie. River Flow Modelling Based on Fuzzy Labels. In: Information Processing and Management of Uncertainty (IPMU 04), July 2004.

• Jonathan Lawry. A Framework for Linguistic Modelling. Artificial Intelligence,volume 155: 1--39, June 2004.

• Jonathan Lawry, J. W. Hall and R. Bovey. Fusion of Expert and Learnt Knowledge in a Framework of Fuzzy Labels. International Journal of Approximate Reasoning, vol. 36: 151--198, June 2004.

• Ines Gonzalez, Jonathan Lawry and Jim Baldwin. Induction and Fusion of Fuzzy Prototypes. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, Vol. 12, No. 4 (2004) 409-446,volume 12(4): 409--446, June 2004.

2003

• Nick Randon and Jonathan Lawry. A New Linguistic Prediction Method Based on Random Set Semantics. In: 2003 UK Workshop on Computational Intelligence :81--88. September 2003. (PDF)

• Jonathan Lawry and Jordi Recasens. A Random Set Model for Fuzzy Labels. In: Symbolic and Quantitative Approaches to Reasoning with Uncertainty, Springer, September 2003.

• Nick Randon and Jonathan Lawry. Fuzzy Models for Prediction based on Random Set Semantics. In: EUSFLAT 2003, :659--664. September 2003. (PDF)

• Zengchang Qin and Jonathan Lawry. Linguistic Decision Tree Induction. In: 2003 UK Workshop on Computational Intelligence, :268--271. September 2003. (PDF)

• Ines Gonzalez, Jonathan Lawry and Jim Baldwin. A Hierarchical Linguistic Clustering Algorithm for Prototype Induction. In: Intelligent Systems for Information Processing, :303--314. Elsevier, June 2003.

• Jim W Hall and Jonathan Lawry. Fuzzy Label Methods for Constructing Imprecise Limit State Functions. Structural Safety,volume 28: 317--341, June 2003.

• Jonathan Lawry. Normalizing possibility distributions using t-norms. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems,volume 11(3): 343--360, June 2003.

• Nick Randon and Jonathan Lawry. Probabilistic and Fuzzy methods for Information Fusion in Data Mining. Internation Journal of Intelligent Systems,volume 18: 609--631, June 2003.

• Jonathan Lawry. Random Sets and Appropriateness Degrees for Modelling with Labels. in Modelling with Words. editors J. Lawry, J. Shanahan, A. Ralescu. Lecture Notes in Artificial Intelligence, Vol.  2873 :186--208

2002

• Jonathan Lawry. Label Prototypes for Data Analysis. In: 2002 UK Computational Intelligence Workshop, September 2002.

• Ines Gonzalez, Jonathan Lawry and Jim Baldwin. A Hierarchical Linguistic Clustering Algorithm for Prototype Induction. In: Information Processing and Management of Uncertainty (IPMU 04), July 2002. (PDF)

• Nick Randon and Jonathan Lawry. Linguistic Modelling Using a Semi-Naive Bayes Framework. In: Information Processing and Management of Uncertainty, July 2002. (PDF)

• Jim W Hall and Jonathan Lawry. Random and Fuzzy Set Reliability Analysis. In: 28'th Conference on Coastal Engineering, :2335--2347. World Scientific, July 2002.

• Jonathan Lawry. A New Calculus for Linguistic Prototypes in Data Analysis. In: Soft Methods in Probability, Statistics, and Data Analysis , :116--125. Springer, June 2002.

• Jonathan Lawry and Jordi Recasens. Normalizacion de Distribuciones Posibilisticas Mediante T-Normas. In: ESTYLF 2002 , June 2002. (PDF)

2001

• Jonathan Lawry. A Methodology for Computing with Words. International Journal of Approximate Reasoning,volume 28: 51--89, June 2001.

• Jonathan Lawry. An Alternative Approach to Computing with Words. International Journal of Uncertainty, Fuzziness and Knowledge Based Systems, vol. 9 (Suppl): 3--16, June 2001.

• Jonathan Lawry. Possibilistic Normalisation and Reasoning Under Partial Inconsistency. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, vol. 9(4): 413--436, June 2001.

• Nick  Randon and Jonathan  Lawry.  A Transparent Framework for Data Mining Using Modelling with Words, Proceedings of the 2001 UK Workshop on Computational Intelligence, Sept. 2001.

• Jonathan Lawry.  Label Prototypes for Modelling with Words, Proceedings of NAFIPS2001. (PDF)

• Ines Gonzalez, Jonathan Lawry and Jim Baldwin. A Linguistic Clustering Algorithm for Fuzzy Prototype Induction, Proceedings of NAFIPS2001.

• Jonathan Lawry.  Label Semantics: A Formal Framework for Modelling with Words. (proceedings of ECSQARU-2001)(Eds. Salem Benferhat, Philippe Besnard), Lecture Notes in Artificial Intelligence, 2143 :374--385.

• Jonathan Lawry.  Query Evaluation from Linguistic Prototypes, Proceedings of 10'th IEEE International Conference on Fuzzy Systems. (PDF)

• Jim Hall and Jonathan Lawry.  Imprecise Probabilities of Engineering System Failure from Random and Fuzzy Set Reliability Analysis, Proceedings of the Second International Symposium on Imprecise Probabilities and their Applications. (PDF)

2000

• Jim Baldwin and Jonathan Lawry.  A New Approach to Learning Linguistic Control Rules, International Journal of Uncertainty Fuzziness and Knowledge Based Systems, Vol.8 No.1 :21--44.

• Ines Gonzalez, Jonathan Lawry and Jim Baldwin (2000), Fuzzy Prototype Induction, UK fuzzy Workshop, Sheffield.

• Jonathan Lawry. An Alternative Interpretation of Linguistic Variables and Computing with Words, proceedings IPMU2000, Vol 3 :1743--1750. ( PDF)

• Jim Baldwin, Jonathan Lawry. A C-FuzzyMeans Algorithm for Prototype Induction, proceedings of FUZZ-IEEE2000, Vol. 1 :164--169. (PDF)

• Jim Baldwin, Jonathan Lawry, Trevor Martin  Mass Assignment based Induction of Linguistic Decision Trees, in Uncertainty in Intelligent and Information Systems (ed. B. Bouchon- Meunier, R.R. Yager, L.A. Zadeh), World Scientific

1999

• Jim Baldwin, Jonathan Lawry and Trevor Martin. A Mass Assignment Method for Prototype Induction,  International Journal of Intelligent Systems, Vol. 14, No. 10 :1041--1070.

1998

• Jonathan Lawry. A Voting Mechanism for Fuzzy Logic, International Journal of Approximate Reasoning Vol. 19, No. 3-4 :315--333.

• Jim Baldwin, Jonathan Lawry and Trevor Martin. A Note on the Conditional Probability of Subsets of a Continuous Domain , Fuzzy Sets and Systems Vol.96 No.2 :221--222.

• Jim Baldwin, Jonathan Lawry and Trevor Martin. The Application of Generalised Fuzzy Rules to Machine Learning and Automated Knowledge Discovery,  International Journal of Uncertainty Fuzziness and Knowledge-Based Systems, Vol. 6 No.5 :459--487.

• Jim Baldwin, Jonathan Lawry and Trevor Martin  Mass Assignment Based Induction of Decision Trees on Words, proceedings of IPMU 98 ( PS)

1997

• Jim Baldwin, Jonathan Lawry, Trevor Martin A Mass Assignment Based ID3 Algorithm for Decision Tree Induction, International Journal of Intelligent Systems Vol. 12 No. 7 :523--552.

• Jonathan Lawry  An Inductive Method for Inexact Reasoning , International Journal of Approximate Reasoning Vol. 16, No.2 :205--221.

• Jim Baldwin, Jonathan Lawry and Trevor Martin (1997) Mass Assignment Fuzzy ID3 with Applications , Proceedings of the unicom workshop on Fuzzy Logic: Applications and Future Directions, London :278--294. (PDF)

1996

• Jim Baldwin, Jonathan Lawry and Trevor Martin. A Mass Assignment Theory of the Probability of Fuzzy Events ,Fuzzy Sets and Systems Vol. 83 No.3 :353--368.

• Jim Baldwin, Jonathan Lawry and Trevor Martin. Efficient Algorithms for Semantic Unification , proceedings of IPMU 96 (the conference of Information Processing and Management of Uncertainty), Granada, Spain.

• Jim Baldwin, Jonathan Lawry and Trevor Martin  A Note on Probability / Possibility Consistency for Fuzzy Events, proceedings of IPMU 96 (the conference of Information Processing and Management of Uncertainty), Granada, Spain (PDF)

1994

• Jonathan Lawry and George Wilmers  An Axiomatic Approach to Systems of Prior Distributions in Inexact Reasoning, Knowledge Representation and Reasoning Under Uncertainty, Lecture Notes in Artificial Intelligence (ed Masuch M, Laszlo P) Vol 808 :81-89

PhD Thesis

• J Lawry Phd Thesis, Manchester (1994) Natural Distributions in Inexact Reasoning (PDF)