Moonis Ali

Colin Fyfe

Nicolás García-Pedrajas

José Manuel Benítez Sánchez

Francisco Herrera Triguero

The three volume set LNAI 6096, LNAI 6097, and LNAI 6098 constitutes the thoroughly refereed conference proceedings of the 23rd International Conference on Industrial Engineering and Other Applications of Applied Intelligend Systems, IEA/AIE 2010, held in Cordoba, Spain, in June 2010.The total of 119 papers selected for the proceedings were carefully reviewed and selected from 297 submissions.

23rd International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2010, Cordoba, Spain, June 1-4, 2010, Proceedings

Trends in Applied Intelligent Systems

Luis Magdalena

Jorge Casillas

O. Cordón

Fuzzy modeling usually comes with two contradictory requirements: interpretability, which is the capability to express the real system behavior in a comprehensible way, and accuracy, which is the capability to faithfully represent the real system. In this framework, one of the most important areas is linguistic fuzzy modeling, where the legibility of the obtained model is the main objective. This task is usually developed by means of linguistic (Mamdani) fuzzy rule-based systems. An active research area is oriented towards the use of new techniques and structures to extend the classical, rigid linguistic fuzzy modeling with the main aim of increasing its precision degree. Traditionally, this accuracy improvement has been carried out without considering the corresponding interpretability loss. Currently, new trends have been proposed trying to preserve the linguistic fuzzy model description power during the optimization process. Written by leading experts in the field, this volume collects some representative researcher that pursue this approach.

Accuracy Improvements in Linguistic Fuzzy Modeling

Fuzzy modeling has become one of the most productive and successful results of fuzzy logic. Among others, it has been applied to knowledge discovery, automatic classification, long-term prediction, or medical and engineering analysis. The research developed in the topic during the last two decades has been mainly focused on exploiting the fuzzy model flexibility to obtain the highest accuracy. This approach usually sets aside the interpretability of the obtained models. However, we should remember the initial philosophy of fuzzy sets theory directed to serve the bridge between the human understanding and the machine processing. In this challenge, the ability of fuzzy models to express the behavior of the real system in a comprehensible manner acquires a great importance. This book collects the works of a group of experts in the field that advocate the interpretability improvements as a mechanism to obtain well balanced fuzzy models.

Interpretability Issues in Fuzzy Modeling

Francisco Herrera Triguero

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