Data Preparation for Fuzzy Modelling using Intervals

Arthur Yosef, Moti Schneider, Eli Shnaider, Amos Baranes, Rimona Palas

2019

Abstract

Model-building professionals are often facing a very difficult choice of selecting relevant variable/s from a set of several similar variables. All those variables are supposedly representing the same factor but are measured differently. They are based on different methodologies, baselines, conversion/comparability methods, etc., thus leading to substantial differences in numerical values for essentially the same things. In this study we introduce a method that utilizes intervals to capture all the relevant variables that represent the same factor. First, we discuss the advantages utilizing intervals of values from the stand point of reliability, better and more efficient data utilization, as well as substantial reduction in the complexity, and thus improvement in our ability to interpret the results. In addition, we introduce an interval (range) reduction algorithm, designed to reduce excessive size of intervals, thus bringing them closer to their central tendency cluster. Following the theoretical component, we present a case study. The case study demonstrates the process of converting the data into intervals for two broad economic variables (each consisting of several data series) and two broad financial variables. Furthermore, it demonstrates the practical application of the procedures addressed in this study and their effectiveness.

Paper Citation

in Harvard Style

Yosef A., Schneider M., Shnaider E., Baranes A. and Palas R. (2019). Data Preparation for Fuzzy Modelling using Intervals. In Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - Volume 1: KDIR; ISBN 978-989-758-382-7, SciTePress, pages 247-257. DOI: 10.5220/0007947102470257

in Bibtex Style

@conference{kdir19,
author={Arthur Yosef and Moti Schneider and Eli Shnaider and Amos Baranes and Rimona Palas},
title={Data Preparation for Fuzzy Modelling using Intervals},
booktitle={Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - Volume 1: KDIR},
year={2019},
pages={247-257},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007947102470257},
isbn={978-989-758-382-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - Volume 1: KDIR
TI - Data Preparation for Fuzzy Modelling using Intervals
SN - 978-989-758-382-7
AU - Yosef A.
AU - Schneider M.
AU - Shnaider E.
AU - Baranes A.
AU - Palas R.
PY - 2019
SP - 247
EP - 257
DO - 10.5220/0007947102470257
PB - SciTePress