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Book Details

  New Book

Artificial Higher Order Neural Networks for Economics and Business


By ZHANG  (Author)
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Price : $180.00  $144.00
ISBN : 9781599048970  
Page : 542
Year of Publication : 2009    Edition : 1
Publisher : INFORMATION SCIENCE REFERENCE
Subject : COMPUTER SCIENCE - IT



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Description :

Artificial Higher Order Neural Networks (HONNs) significantly change the research methodology that is used in economics and business areas for nonlinear data simulation and prediction. With the important advances in HONNs, it becomes imperative to remain knowledgeable about its benefits and improvements.

Artificial Higher Order Neural Networks for Economics and Business is the first book to provide practical education and applications for the millions of professionals working in economics, accounting, finance and other business areas on HONNs and the ease of their usage to obtain more accurate application results. This source provides significant, informative advancements in the subject and introduces the concepts of HONN group models and adaptive HONNs.



Content :

Preface

Acknowledgment

Section I

Artificial Higher Order Neural Networks for Economics

Chapter I Artificial Higher Order Neural Network Nonlinear Models: SAS NLIN or HONNs?

Chapter II Higher Order Neural Networks with Bayesian Confidence Measure for the Prediction of the EUR/USD Exchange Rate

Chapter III Automatically Identifying Predictor Variables for Stock Return Prediction

Chapter IV Higher Order Neural Network Architectures for Agent-Based Computational Economics and Finance

Chapter V Foreign Exchange Rate Forecasting Using Higher Order Flexible Neural Tree

Chapter VI Higher Order Neural Networks for Stock Index Modeling

Section II

Artificial Higher Order Neural Networks for Time Series Data

Chapter VII Ultra High Frequency Trigonometric Higher Order Neural Networks for Time Series Data Analysis

Chapter VIII Artificial Higher Order Pipeline Recurrent Neural Networks for Financial Time Series Prediction

Chapter IX A Novel Recurrent Polynomial Neural Network for Financial Time Series Prediction

Chapter X Generalized Correlation Higher Order Neural Networks for Financial Time Series Prediction

Chapter XI Artificial Higher Order Neural Networks in Time Series Prediction

Chapter XII Application of Pi-Sigma Neural Networks and Ridge Polynomial Neural Networks to Financial Time Series Prediction

Section III

Artificial Higher Order Neural Networks for Business

Chapter XIII Electric Load Demand and Electricity Prices Forecasting Using Higher Order Neural Networks Trained by Kalman Filtering

Chapter XIV Adaptive Higher Order Neural Network Models and Their Applications in Business

Chapter XV CEO Tenure and Debt: An Artificial Higher Order Neural Network Approach

Chapter XVI Modelling and Trading the Soybean-Oil Crush Spread with Recurrent and Higher Order Networks: A Comparative Analysis

Section IV

Artificial Higher Order Neural Networks Fundamentals

Chapter XVII Fundamental Theory of Artificial Higher Order Neural Networks

Chapter XVIII Dynamics in Artificial Higher Order Neural Networks with Delays

Chapter XIX A New Topology for Artificial Higher Order Neural Networks: Polynomial Kernel Networks

Chapter XX High Speed Optical Higher Order Neural Networks for Discovering Data Trends and Patterns in Very Large Databases

Chapter XXI On Complex Artificial Higher Order Neural Networks: Dealing with Stochasticity, Jumps and Delays

Chapter XXII Trigonometric Polynomial Higher Order Neural Network Group Models and Weighted Kernel Models for Financial Data Simulation and Prediction

About the Contributors

Index

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