Artificial neural networks in finance and manufacturing

Author(s)

Bibliographic Information

Artificial neural networks in finance and manufacturing

Joarder Kamruzzaman, Rezaul K. Begg, Ruhul A. Sarker

Idea Group Pub., c2006

  • : hbk

Available at  / 2 libraries

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Note

Includes bibliographical references and index

Description and Table of Contents

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.

Table of Contents

  • A Sample of Contents: Artificial Neural Networks: Applications in Finance and Manufacturing
  • Hybrid-learning Methods for Stock-index Modeling.

by "Nielsen BookData"

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