Titlebook: Interpretability Issues in Fuzzy Modeling; Jorge Casillas,Oscar Cordón,Luis Magdalena Book 2003 Springer-Verlag Berlin Heidelberg 2003 aut

壓倒性勝利

Singular Value-Based Fuzzy Reduction With Relaxed Normality Conditionthe rule consequents and eliminates the weak and redundant components according to the magnitudes of the resulting singular values. The number of reduced rules as resulted depends on the number of singular values retained in the process. Conditions of sum normalization (SN), non-negativeness (NN) an

Horizon

Book 2003 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 interpretabilit

斗爭

GREG

A Multiobjective Genetic Learning Process for joint Feature Selection and Granularity and Contexts Liate granularity for each of them. An ad-hoc data covering learning method is considered to obtain the Rule Base. The method uses a multiobjective genetic algorithm in order to obtain a good trade-off between accuracy and interpretability.

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Constrained Optimization of Fuzzy Decision Treestions on input variable domains. The membership functions are automatically placed thanks to an evolutionary strategy. We propose also a heuristics in order to find a sub-optimal structure of the tree.

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bacteria

A new method for inducing a set of interpretable fuzzy partitions and fuzzy inference systems from depresented by a group of rules. The simplification tolerates some loss of accuracy while being guided by indices complementary to the usual numerical performance index..The proposed approach is applied to a rice quality evaluation problem.

瑪瑙

Effect of Rule Representation in Rule Base Reductionduce fuzzy models of acceptable precision with a small number of rules. A set of experiments has been performed to compare the effect of the rule representation on the ability to reduce the number of rules and on the precision of the resulting models.

Leaven

Extracting Linguistic Fuzzy Models from Numerical Data-AFRELI Algorithmented with the use of the Fu Zion algorithm created to merge consecutive membership functions while guar anteeing the distinguishability between fuzzy sets. Examples of function approximations and modeling of industrial data are presented as application examples.