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
收藏
页码：115 / 120
页数：6
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