Wyniki wyszukiwania - BazTech

Ograniczanie wyników

Znaleziono wyników: 2

Liczba wyników na stronie

Wyniki wyszukiwania

Wyszukiwano:
w słowach kluczowych: fuzzy association rules

Sortuj według:

Ogranicz wyniki do:

Evolutionary algorithms and fuzzy sets for discovering temporal rules

Matthews S. G., Gongora M. A., Hopgood A. A.

International Journal of Applied Mathematics and Computer Science

2013

Vol. 23, no. 4

855--868

A novel method is presented for mining fuzzy association rules that have a temporal pattern. Our proposed method contributes towards discovering temporal patterns that could otherwise be lost from defining the membership functions before the mining process. The novelty of this research lies in exploring the composition of fuzzy and temporal association rules, and using a multi-objective evolutionary algorithm combined with iterative rule learning to mine many rules. Temporal patterns are augmented into a dataset to analyse the method’s ability in a controlled experiment. It is shown that the method is capable of discovering temporal patterns, and the effect of Boolean itemset support on the efficacy of discovering temporal fuzzy association rules is presented.

Probabilistic-fuzzy knowledge-based system for managerial applications

Rudnik K., Walaszek-Babiszewska A.

Management and Production Engineering Review

2012

Vol. 3, No. 1

49-61

The paper deals with an inference system with probabilistic-fuzzy knowledge base as a tool which can help users in analyzing complete uncertainty of real problems in the company using fuzzy sets and probability. In the mentioned system, knowledge is saved in the weighted IFTHEN fuzzy rules, where the weights constitute marginal probabilities of the fuzzy events in the antecedents and conditional probabilities of the fuzzy events in the consequents. Moreover, the paper presents a proposal of the use of fuzzy association rules as a method of automatic knowledge base extraction in the inference system. For this purpose a modification of the PF-Growth algorithm is described. A numerical example is analyzed by using wind speed prediction process. The correct estimation of wind speed, as the potential energy resource, is necessary for control of the wind turbine work and it is important for the localization process of wind turbines, production planning and estimating cost-effectiveness of such investments.