Book description
Two of the most important factors contributing to national and
international economy are processing of information for accurate financial
forecasting and decision making as well as processing of information for
efficient control of manufacturing systems for increased productivity. The
associated problems are very complex and conventional methods often fail to
produce acceptable solutions. Moreover, businesses and industries always
look for superior solutions to boost profitability and productivity. In
recent times, artificial neural networks have demonstrated promising results
in solving many real-world problems in these domains, and these techniques
are increasingly gaining business and industry acceptance among the
practitioners.
Artificial Neural Networks in Finance and Manufacturing presents many
state-of-the-art and diverse applications to finance and manufacturing,
along with underlying neural network theories and architectures. It offers
researchers and practitioners the opportunity to access exciting and
cutting-edge research focusing on neural network applications, combining two
aspects of economic domain in a single and consolidated volume.
About the author
Dr. Kamruzzaman is a senior lecturer in the Faculty of Information
Technology at Monash University. His research interest includes
computational intelligence, computer networks and bioinformatics. He has
published more than 90 refereed papers in international journals and
conference proceedings.
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