This paper proposes fuzzy modeling using obtained data. Fuzzy system is known as knowledge-based or rule-bases system. The most important part of fuzzy system is rule-base. One of problems of generation of fuzzy rule with training data is inconsistence data. Existence of inconsistence and uncertain states in training data causes high error in modeling. Here, Probability fuzzy system presents to...

This study proposes a modified version of cultural algorithms (CAs) which benefits from rule-based system for influence function. This rule-based system selects and applies the suitable knowledge source according to the distribution of the solutions. This is important to use appropriate influence function to apply to a specific individual, regarding to its role in the search process. This rule ...

This paper presents a prototype of case-based reasoning, built for the agricultural domain. Its aim is to forecast the allocation of a new energy crop, the miscanthus. Interviews were conducted with french farmers in order to know how they make their decisions. Based on interview analysis, a case base and a rule base have been formalized, together with similarity and adaptation knowledge. Furth...

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Dynamic changes of object positions provide an important clue for video characterization. In the present work, we exploit the dynamic information present over different frames of a sports video to characterize the change in the configuration of players across different frames. For scene dynamic characterization firstly location of players are detected by using motion based segmentation. We then...

Maintenance of association rules is an interesting problem. Several incremental maintenance algorithms were proposed since the work of (Cheung et al, 1996). The majority of these algorithms maintain rule bases assuming that support threshold doesn't change. In this paper, we present incremental maintenance algorithm under support threshold change. This solution allows user to maintain its rule ...

Fuzzy inference process usually involves the use of fuzzy rule base consisting in several fuzzy rules. Overall output can be obtained by aggregation of outputs of all rules. To obtain an output of individual rule the relevancy of this rule is calculated. Then the individual output is obtained from the relevancy and the consequent of the rule. Such process can be realised using an operator that ...

Abstract. This paper presents the synthesis and analysis of the enhanced predictive fuzzy Hammerstein model of the water tank system. Fuzzy Hammerstein model was compared with three other fuzzy models: the first was synthesized using Mamdani type rule base, the second – Takagi-Sugeno type rule base and the third – composed of Mamdani and Takagi-Sugeno rule bases. The synthesized model is invert...

In the 3eld of fuzzy modelling, the exclusive consideration of the modelling error leads to problems concerning the handling of high-dimensional applications and the interpretability of the resulting rule base. To solve those problems, a statistically motivated fuzzy rule test is proposed. It decides if a fuzzy IF=THEN statement is a relevant rule or not. In this way, the problem of 3nding a go...