Enhanced Equal Frequency Partition Method for the
Identification of a Water Demand System
Keywords
- Unsupervised Partitioning
- Fuzzy Inductive Reasoning
- Water Demand System
Abstract
This paper deals with unsupervised partitioning. A first goal of
this paper is to present an enhancement to the Equal Frequency
Partition (EFP) method that allows to reduce, to some extent,
the main drawback of this classical classication method, i.e., the
data distribution dependency. A second goal of this work is to
use the Enhanced Equal Frequency Partition (EEFP) method
within the discretization process of the Fuzzy Inductive
Reasoning (FIR) methodology for the identification of a model
of a water demand system. It is shown that use of the EEFP method
allows to obtain more accurate FIR models of the water demand
system, reducing the prediction errors.
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Last modified: May 29, 2007 -- © François Cellier