@inproceedings{127e58f199de4e958a506e8352060d6c,
title = "Multiple Function Approximation - A New Approach Using Complex Fuzzy Inference System",
abstract = "A complex-fuzzy machine learning approach to function approximation for multiple functions is proposed in this paper. The proposed approach involves the utility of complex-valued vector outputs by a novel complex-fuzzy model using complex fuzzy sets and the famous PSO-RLSE hybrid algorithm for machine learning of the model. An experiment was used to test the proposed approach for the ability of approximating four functions simultaneously. With the experimental result, the performance by the proposed model is promising and the proposed approach is compared to other methods. With complex fuzzy sets, the proposed approach has shown the excellent capability of function approximation for multiple functions using one single model with good performance.",
keywords = "Complex fuzzy set, Function approximation, Fuzzy system, Multi-target prediction",
author = "Tu, {Chia Hao} and Chunshien Li",
note = "Publisher Copyright: {\textcopyright} 2018, Springer International Publishing AG, part of Springer Nature.; 10th International scientific conferences on research and applications in the field of intelligent information and database systems, ACIIDS 2018 ; Conference date: 19-03-2018 Through 21-03-2018",
year = "2018",
doi = "10.1007/978-3-319-75417-8_23",
language = "???core.languages.en_GB???",
isbn = "9783319754161",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "243--254",
editor = "Hoang Pham and Nguyen, {Ngoc Thanh} and Bogdan Trawinski and Hoang, {Duong Hung} and Tzung-Pei Hong",
booktitle = "Intelligent Information and Database Systems - 10th Asian Conference, ACIIDS 2018, Proceedings",
}