Type-2 Fuzzy Clustering and a Type-2 Fuzzy Inference Neural Network for the Prediction of Short-Term Interest Rates

被引：5

作者：

Enke, David ^{[1
]}

Mehdiyev, Nijat ^{[2
,3
]}

机构：

[1] Missouri Univ Sci & Technol, Dept Engn Management & Syst Engn, Rolla, MO 65409 USA

[2] Univ Augsburg, Dept Finance & Informat Management, D-86159 Augsburg, Germany

[3] Tech Univ Munich, Dept Finance & Informat Management, D-80290 Munich, Germany

来源：

COMPLEX ADAPTIVE SYSTEMS: EMERGING TECHNOLOGIES FOR EVOLVING SYSTEMS: SOCIO-TECHNICAL, CYBER AND BIG DATA | 2013年 / 20卷

关键词：

Multiple Regression Analysis; Differential Evoultion; Type-2 Fuzzy Systems; Interest Rate Forecasting; REGRESSION;

D O I：

10.1016/j.procs.2013.09.248

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The following paper discusses the use of a hybrid model for the prediction of short-term US interest rates. The model consists of a differential evolution-based fuzzy type-2 clustering with a fuzzy type-2 inference neural network, after input preprocessing with multiple regression analysis. The model was applied to forecast the US 3-Month T-bill rates. Promising model performance was obtained as measured using root mean square error. (C) 2013 The Authors. Published by Elsevier B.V.

引用

页码：115 / 120

页数：6

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