Artificial Higher Order Neural Networks for Economics and Business Premier Reference Source

Ming Zhang

ISBN 10: 1599048973 / ISBN 13: 9781599048970

Published by IGI Global, 2008

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Bibliographic Details

Title: Artificial Higher Order Neural Networks for ...

Publisher: IGI Global

Publication Date: 2008

Binding: HRD

Condition: New

About this title

Synopsis:

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.

About the Author:

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.