@inproceedings{7389058c770f4ae58be81ca61273dea7,
title = "Curvature-Based Sparse Rule Base Generation for Fuzzy Interpolation Using Menger Curvature",
abstract = "Fuzzy interpolation improves the applicability of fuzzy inference by allowing the utilisation of sparse rule bases. Curvature-based rule base generation approach has been recently proposed to support fuzzy interpolation. Despite the ability to directly generating sparse rule bases from data, the approach often suffers from the high dimensionality of complex inference problems. In this work, a different curvature calculation approach, i.e., the Menger approach, is employed to the curvature-based rule base generation approach in an effort to address the limitation. The experimental results confirm better efficiency and efficacy of the proposed method in generating rule bases on high-dimensional datasets.",
keywords = "Fuzzy interpolation, High-dimensional data, Menger curvature, Rule base generation, Sparse rule base",
author = "Zheming Zuo and Jie Li and Longzhi Yang",
year = "2020",
month = jan,
day = "1",
doi = "10.1007/978-3-030-29933-0_5",
language = "English",
isbn = "9783030299323",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer",
pages = "53--65",
editor = "Zhaojie Ju and Dalin Zhou and Alexander Gegov and Longzhi Yang and Chenguang Yang",
booktitle = "Advances in Computational Intelligence Systems - Contributions Presented at the 19th UK Workshop on Computational Intelligence, 2019",
address = "Germany",
note = "19th Annual UK Workshop on Computational Intelligence, UKCI 2019 ; Conference date: 04-09-2019 Through 06-09-2019",
}