LOGICAL AGGREGATION FOR MODULAR NEURAL NETWORKS IN CURRENCY EXCHANGE RATE FORECASTING

被引：0
|
作者：
Nesic, Ivan [1 ]
Rakicevic, Aleksandar [1 ]
Petrovic, Bratislav [1 ]
Radojevic, Dragan [2 ]
机构：
[1] Univ Belgrade, Fac Org Sci, Jove Ilica 154, Belgrade 11000, Serbia
[2] Mihailo Pupin Inst, Belgrade 11000, Serbia
来源：
UNCERTAINTY MODELING IN KNOWLEDGE ENGINEERING AND DECISION MAKING | 2012年 / 7卷
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D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper fields of research are modular neural networks and consistent real-valued logic as a technique for aggregation of the modules. Aggregation is done using logical and pseudo-logical aggregation based on interpolative Boolean algebra (IBA). IBA is technically realized through generalized Boolean polynomials. The proposed technique expands the existing base of modular neural network models and shows respectable results in forecasting currency exchange rates
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页码：573 / 578
页数：6
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