Fuzzy inference systems: An integrated modeling environment for collaboration between expert knowledge and data using FisPro

Expert Systems with Applications

Volumn 39, Issue 10, 2012, Pages 8744-8755

  Guillaume, Serge ^a   Charnomordic, Brigitte ^b  

^a UMR ITAP   (France)

^b UMR 729 MISTEA   (France)

Author keywords

Cooperation; Fuzzy logic; Knowledge formalization; Open source software; Real word applications; Rule learning

Indexed keywords

COOPERATION; EXPERT KNOWLEDGE; FUZZY INFERENCE SYSTEMS; HUMAN INTERACTIONS; INTEGRATED MODELING ENVIRONMENT; KNOWLEDGE FORMALIZATION; OPEN SOURCE SOFTWARE; RULE LEARNING; SOFTWARE UTILITIES; SYSTEM MODELING;

FUZZY LOGIC; FUZZY SYSTEMS;

UTILITY PROGRAMS;

EID: 84859270665     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2012.01.206     Document Type: Article

References (61)

1. G. Adomavicius, and A. Tuzhilin Expert-driven validation of rule-based user models in personalization applications Data Mining and Knowledge Discovery 5 1-2 2001 33 58
2. Alonso, J. M. (2010). Guaje: Generating understandable and accurate fuzzy models in a java environment. http://www.softcomputing.es/guaje.
3. J.M. Alonso, L. Magdalena, and G. González-Rodríguez Looking for a good fuzzy system interpretability index: An experimental approach International Journal of Approximate Reasoning 51 1 2009 115 134
4. J.M. Alonso, L. Magdalena, and S. Guillaume Hilk: A new methodology for designing highly interpretable linguistic knowledge bases using the fuzzy logic formalism International Journal of Intelligent Systems 23 7 2008 761 794
5. Aptronics. (2007). Fide power design tool http://www.aptronix.com.
6. R. Babuška Neuro-fuzzy methods for modeling and identification 2003 Physica-Verlag GmbH Heidelberg, Germany
7. Baturone, I.; Moreno-Velo, F. J.; Sánchez-Solano, S.; Barrios, A. B.; Jiménez, P. B.; Gersnoviez, A.; Brox, M. (2007). Using xfuzzy environment for the whole design of fuzzy systems. In IEEE (2007) (pp. 517-522).
8. L.M. Bergasa, J. Nuevo, M.A. Sotelo, R. Barea, and M.E. Lopez Real-time system for monitoring driver vigilance IEEE Transactions on Intelligent Transportation Systems 7 1 2006 63 77
9. J.C. Bezdek Pattern recognition with fuzzy objective functions algorithms 1981 Plenum Press New York
10. Borgelt, C.; Gonzáles-Rodríguez, G. (2007). Frida - A free intelligent data analysis toolbox. In IEEE (2007) (pp. 1892-1896).
11. T. Bossomaier, R.K. Standish, and M. Harré Simulation of trust in client-wealth management adviser relationships International Journal of Simulation and Process Modelling 6 1 2010 40 49
12. Breiman, L.; Friedman, J. H.; Olshen, R. A.; Stone, C. J. (1984). Classification and Regression Trees. Wadsworth International Group, Belmont CA.
13. J. Casillas, O. Cordón, F. Herrera, and L. Magdalena Interpretability improvements to find the balance interpretability-accuracy in fuzzy modeling: An overview Interpretability issues in fuzzy modeling 2003 Springer pp. 3-22
14. S. Chen, S.A. Billings, and W. Luo Orthogonal least squares methods and their application to non-linear system identification Int. J. Control 50 1989 1873 1896
15. S. Chen, C.F.N. Cowan, and P.M. Grant Orthogonal least squares learning algorithm for radial basis function networks IEEE Transactions on Neural Networks 2 No 2 1991 302 309
16. S. Destercke, S. Guillaume, and B. Charnomordic Building an interpretable fuzzy rule base from data using orthogonal least squares- application to a depollution problem Fuzzy Sets and Systems 158 2007 2078 2094
17. D. Dubois, and H. Prade What are fuzzy rules and how to use them Fuzzy Sets and Systems 84 2 1996 169 186
18. D. Dubois, and H. Prade The three semantics of fuzzy sets Fuzzy Sets and Systems 90 1997 141 150
19. D. Dubois, and H. Prade Fuzzy set and possibility theory-based methods in artificial intelligence Artificial Intelligence 148 2003 1 9
20. D. Dubois, H. Prade, and L. Ughetto Checking the coherence and redundancy of fuzzy knowledge bases IEEE Trans. on Fuzzy Systems 5 5 1997 398 417
21. D. Dubois, H. Prade, and L. Ughetto A new perspective on reasoning with fuzzy rules International Journal of Intelligent Systems 18 2003 541 567
22. Foulloy, L.; Galichet, S.; Boukezzoula, R. (2005). Floulib. http://www.polytech.univ-savoie.fr/index.php?id=859.
23. Y. Gil, C. Sinfort, S. Guillaume, Y. Brunet, and B. Palagos Influence of micrometeorological factors on pesticide loss to the air during vine spraying: Data analysis with statistical and fuzzy inference models Biosystems Engineering 100 2 2008 184 197
24. P.-Y. Glorennec Constrained optimization of FIS using an evolutionary method Genetic algorithms and soft computing 1996 Physica-Verlag pp. 349-368
25. Glorennec, P. -Y. (1999). Algorithmes d'apprentissage pour systmes d'inférence floue. Editions Herms, Paris.
26. GmbH, M. (2001). Dataengine. http://www.dataengine.de.
27. GmbH, I. (2007). Fuzzytech. http://www.fuzzytech.com.
28. S. Guillaume Designing fuzzy inference systems from data: An interpretability-oriented review IEEE Transactions on Fuzzy Systems 9 3 2001 426 443
29. S. Guillaume, and B. Charnomordic Generating an interpretable family of fuzzy partitions IEEE Transactions on Fuzzy Systems 12 3 2004 324 335
30. S. Guillaume, and B. Charnomordic Learning interpretable fuzzy inference systems with fispro International Journal of Information Sciences 181 2011 4409 4427
31. S. Guillaume, and L. Magdalena Expert guided integration of induced knowledge into a fuzzy knowledge base Soft computing 10 9 2006 773 784
32. Hohensohn, J.; Mendel, J. M. (1994). Two pass orthogonal least-squares algorithm to train and reduce fuzzy logic systems. In Proceedings of IEEE Conference on Fuzzy Systems Orlando, Florida (pp. 696-700).
33. E. Hullermeier Fuzzy methods in machine learning and data mining: Status and prospects Fuzzy sets and Systems 156 2005 387 406
34. IEEE (Ed.), (2007). FUZZ-IEEE 2007, IEEE International Conference on Fuzzy Systems, Imperial College, London, UK, 23-26 July, 2007, Proceedings of IEEE.
35. InfraLogic, T. (1995). The world's source for fuzzy logic solutions http://www.ortech-engr.com/fuzzy/togai.html.
36. Janikow, C. Z. (2005). Fuzzy decision tree/forest. http://www.cs.umsl. edu/janikow/fid/.
37. H. Jones, B. Charnomordic, D. Dubois, and S. Guillaume Practical inference with systems of gradual implicative rules IEEE Transactions on Fuzzy Systems 17 1 2009 61 78
38. Kruse, R. (2007). Neural networks and fuzzy systems. http://fuzzy.cs.uni- magdeburg.de/.
39. C.C. Lee Fuzzy logic in control systems: Fuzzy logic controller-part ii IEEE Trans. on Systems, Man, and Cybernetics 20 2 1990 419 435
40. Ling, T.; Kang, B. H.; Johns, D. P.; Walls, J.; Bindoff, I. (2008). Expert-driven knowledge discovery. In Latifi, S. (Ed.), Proceedings of the fifth international conference on information technology: New generations (pp. 174-178).
41. E.H. Mamdani, and S. Assilian An experiment in linguistic synthesis with a fuzzy logic controller International journal of Man-Machine Studies 7 1975 1 13
42. R. Martin-Clouaire Semantic and computation of the generalized modus ponens: The long paper International Journal of Approximate Reasoning 3 2 1989 195 217
43. MathWorks. (2007). Fuzzy logic toolbox http://www.mathworks.com/products/ fuzzylogic.
44. Nauck, D. D. (2007). Gnu fuzzy. In IEEE (2007) (pp. 1019-1024).
45. Orchard, R. A. (2004). Fuzzy extension to the clips expert system shell (fuzzyclips). http://www.nrc-cnrc.gc.ca/fra/licences/iti/non-commerciale9.html.
46. J.R. Quinlan Induction of decision trees Machine Learning 1 1986 81 106
47. T. Rajaram, and A. Das Modeling of interactions among sustainability components of an agro-ecosystem using local knowledge through cognitive mapping and fuzzy inference system Expert Systems with Applications 37 2 2010 1734 1744
48. Research, W. (2007). Mathematica fuzzy logic http://www.wolfram.com/ products/applications/fuzzylogic.
49. E.H. Ruspini Recent developments in fuzzy clustering 1982 Pergamon Press New York (pp. 133-147)
50. Sazonov, E. (2002). Open source fuzzy inference engine for java http://people.clarkson.edu/esazonov/FuzzyEngine.htm.
51. M. Sester Knowledge acquisition for the automatic interpretation of spatial data International Journal of Geographical Information Science 14 1 2000 1 24
52. F.J. Solis, and R.J. Wets Minimization by random search techniques Mathematics of Operation Research 6 1981 19 30
53. T. Takagi, and M. Sugeno Fuzzy identification of systems and its applications to modeling and control IEEE Transactions on System Man and Cybernetics 15 1985 116 132
54. J.V. Valente de Oliveira Semantic constraints for membership functions optimization IEEE Transactions on Systems, Man and Cybernetics. Part A 29 1 1999 128 138
55. L.-X. Wang, and J.M. Mendel Fuzzy basis functions, universal approximation, and orthogonal least squares learning IEEE Transactions on Neural Networks 3 1992 807 814
56. L.-X. Wang, and J.M. Mendel Generating fuzzy rules by learning from examples IEEE Transactions on Systems, Man and Cybernetics 22 6 1992 1414 1427
57. Weber, R. (1992). Fuzzy-id3: A class of methods for automatic knowledge acquisition. In 2nd International conference on fuzzy logic and neural networks (pp. 265-268).
58. J. Weisbrod A new approach to fuzzy reasoning Soft Computing 2 1998 89 99
59. L.A. Zadeh Fuzzy sets Information and Control 8 1965 338 353
60. L.A. Zadeh The concept of linguistic variable and its application to approximate reasoning - Parts I, II and III Information Sciences 8-9 1975 301 357 (pp. 43-48)
61. L.A. Zadeh Is there a need for fuzzy logic? Information Sciences 178 13 2008 2751 2779