[show abstract][hide abstract] ABSTRACT: The aim of this paper is to present an algorithm to induce the Temporal Fuzzy Chains (TFCs) (J. Moreno, 2002b). TFCs are used to model the dynamic systems in a linguistic manner. TFCs make use of two different concepts: the traditional method to represent the dynamic systems named state vectors (Ogata, 1998), and the linguistic variables (Zadeh, 1975) used in fuzzy logic (Tanaka, 1998). Thus, TFCs are qualitative and represents the "temporal zones" using linguistic states and linguistic transitions between the linguistic states.
[show abstract][hide abstract] ABSTRACT: Abstract The aim of this paper is to present the Temporal Fuzzy Models (TFMs). These models are used to represent the systems that change in time, i. e., dynamic systems. Temporal fuzzy rules of TFMs are ordered, so each rule represents a ”temporal zone”. An algorithm is presented to obtain the TFM. This algorithm needs as input a fuzzy model based in linguistic labels. An inference method is presented too. Finally, a fuzzy model of a shot put of the Spanish athlete Manuel Martinez is obtained with the direct linguistic induction algorithm  that is used as input. Keywords: Models induction, linguistic models,
Proceedings of the International Conference on Artificial Intelligence, IC-AI '02, June 24 - 27, 2002, Las Vegas, Nevada, USA, Volume 1; 01/2002
Data provided are for informational purposes only. Although carefully collected, accuracy cannot be guaranteed. The impact factor represents a rough estimation of the journal's impact factor and does not reflect the actual current impact factor. Publisher conditions are provided by RoMEO. Differing provisions from the publisher's actual policy or licence agreement may be applicable.