Artificial Higher Order Neural Networks for Economics and Business

Artificial Higher Order Neural Networks for Economics and Business

Ming Zhang
Indexed In: SCOPUS View 2 More Indices
Release Date: July, 2008|Copyright: © 2009 |Pages: 542
DOI: 10.4018/978-1-59904-897-0
ISBN13: 9781599048970|ISBN10: 1599048973|EISBN13: 9781599048987
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Description & Coverage
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.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Accounting HONNs
  • Adaptive HONNs
  • Artificial Higher Order Neural Networks
  • Banking HONNs
  • Business HONNs
  • Economic HONNs
  • Higher order neural network
  • SINC HONNs
  • SINCHONNsim
  • SPHONNsim
  • SXSHONNsim
  • THONNsim
  • Time series prediction
  • Trigonometric HONNs
  • UCSHONNsim
  • Ultra high frequency HONNs
Reviews & Statements

This book discusses how HONNs will challenge SAS NLIN procedures and change the research methodology that people are currently using in economics and business areas for the nonlinear date simulation and prediction.

– Ming Zhang, Christopher Newport University, USA

This book provides practical information on HONNs and their use for professional and advanced students.

– Book News Inc. (Nov. 2008)
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Editor/Author Biographies
Ming Zhang was born in Shanghai, China. He received the MS degree in information processing and PhD degree in the research area of computer vision from East China Normal University, Shanghai, China, in 1982 and 1989, respectively. He held Postdoctoral Fellowships in artificial neural networks with the Chinese Academy of the Sciences in 1989 and the USA National Research Council in 1991. He was a face recognition airport security system project manager and PhD co-supervisor at the University of Wollongong, Australia in 1992. Since 1994, he was a lecturer at the Monash University, Australia, with a research area of artificial neural network financial information system. From 1995 to 1999, he was a senior lecturer and PhD supervisor at the University of Western Sydney, Australia, with the research interest of artificial neural networks. He also held Senior Research Associate Fellowship in artificial neural networks with the USA National Research Council in 1999. He is currently a Full Professor and graduate student supervisor in computer science at the Christopher Newport University, VA, USA. With more than 100 papers published, his current research includes artificial neural network models for face recognition, weather forecasting, financial data simulation, and management.
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