Type-1 and interval type-2 ANFIS: a comparison

In a previous paper, we proposed an extended ANFIS architecture and showed that interval type-2 ANFIS produced larger errors than type-1 ANFIS on the well-known IRIS classification problem. In this paper, more experiments on both synthetic and real-world data are conducted to further investigate and...

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Main Authors: Chen, Chao, John, Robert, Twycross, Jamie, Garibaldi, Jonathan M.
Format: Conference or Workshop Item
Published: 2017
Online Access:https://eprints.nottingham.ac.uk/41808/
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author Chen, Chao
John, Robert
Twycross, Jamie
Garibaldi, Jonathan M.
author_facet Chen, Chao
John, Robert
Twycross, Jamie
Garibaldi, Jonathan M.
author_sort Chen, Chao
building Nottingham Research Data Repository
collection Online Access
description In a previous paper, we proposed an extended ANFIS architecture and showed that interval type-2 ANFIS produced larger errors than type-1 ANFIS on the well-known IRIS classification problem. In this paper, more experiments on both synthetic and real-world data are conducted to further investigate and compare the performance of interval type-2 ANFIS and type-1 ANFIS. For each dataset, interval type-2 ANFIS is optimised in three different ways, including a strategy suggested by Mendel such that interval type-2 ANFIS would be no worse than type-1 ANFIS. Our results show that in some circumstances the performance of interval type-2 ANFIS can be improved when it is initialised with blurred optimised type-1 ANFIS parameters. However, in general, interval type-2 ANFIS does not produce a clear performance improvement compared to type-1 ANFIS, especially on Mackey-Glass data with large noise. Thus, we conclude that the choice of interval type-2 ANFIS over type-1 ANFIS should be carefully considered, since type-2 ANFIS is more computationally complex, yet significantly better performance cannot be easily obtained.
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spelling nottingham-418082020-05-04T19:01:49Z https://eprints.nottingham.ac.uk/41808/ Type-1 and interval type-2 ANFIS: a comparison Chen, Chao John, Robert Twycross, Jamie Garibaldi, Jonathan M. In a previous paper, we proposed an extended ANFIS architecture and showed that interval type-2 ANFIS produced larger errors than type-1 ANFIS on the well-known IRIS classification problem. In this paper, more experiments on both synthetic and real-world data are conducted to further investigate and compare the performance of interval type-2 ANFIS and type-1 ANFIS. For each dataset, interval type-2 ANFIS is optimised in three different ways, including a strategy suggested by Mendel such that interval type-2 ANFIS would be no worse than type-1 ANFIS. Our results show that in some circumstances the performance of interval type-2 ANFIS can be improved when it is initialised with blurred optimised type-1 ANFIS parameters. However, in general, interval type-2 ANFIS does not produce a clear performance improvement compared to type-1 ANFIS, especially on Mackey-Glass data with large noise. Thus, we conclude that the choice of interval type-2 ANFIS over type-1 ANFIS should be carefully considered, since type-2 ANFIS is more computationally complex, yet significantly better performance cannot be easily obtained. 2017-08-24 Conference or Workshop Item PeerReviewed Chen, Chao, John, Robert, Twycross, Jamie and Garibaldi, Jonathan M. (2017) Type-1 and interval type-2 ANFIS: a comparison. In: 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2017), 9-12 July 2017, Naples, Italy. http://ieeexplore.ieee.org/abstract/document/8015555/
spellingShingle Chen, Chao
John, Robert
Twycross, Jamie
Garibaldi, Jonathan M.
Type-1 and interval type-2 ANFIS: a comparison
title Type-1 and interval type-2 ANFIS: a comparison
title_full Type-1 and interval type-2 ANFIS: a comparison
title_fullStr Type-1 and interval type-2 ANFIS: a comparison
title_full_unstemmed Type-1 and interval type-2 ANFIS: a comparison
title_short Type-1 and interval type-2 ANFIS: a comparison
title_sort type-1 and interval type-2 anfis: a comparison
url https://eprints.nottingham.ac.uk/41808/
https://eprints.nottingham.ac.uk/41808/