C++ Neural Networks and Fuzzy Logic: Preface


Hierarchical Neural Network



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C neural networks and fuzzy logic

Hierarchical Neural Network

Mendelsohn developed a multilevel neural network as shown in Figure 14.9. Here five neural networks are

arranged such that four network outputs feed that final network. The four networks are trained to produce the

High, Low, short−term trend, and medium−term trend for a particular financial instrument. The final network

takes these four outputs as input and produces a turning point indicator.

Figure 14.9

  Hierarchical neural network system to predict turning points.

C++ Neural Networks and Fuzzy Logic:Preface

Neural Nets versus Box−Jenkins Time−Series Forecasting

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Each network was trained and tested with 1200 fact days spanning 1988 to 1992 (33% used for testing).

Preprocessing was accomplished by using differences of the inputs and with some technical analysis studies:




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