Artificial neural networks in finance and manufacturing / editores Joarder Kamruzzaman, Rezaul K. Begg y Ruhul A. Sarker.

Incluye índice (284-287)

Chapter I. Artificial neural networks: applications in financeand manufacturing ; Chapter II. Simultaneous evolution of network architectures and connection weights in artificial neural networks ; Chapter III. Neural network-based stock market return forecasting using data mining for variable reduction ; Chapter IV. Hybrid-Learning methods for stock index modeling ; Chapter V. Application of Higher-Order neural networks to financial times-series prediction ; Chapter VI. Hierarchical neural networks for modelling adaptive financial systems ; Chapter VII. Forecasting the term structure of interest rates using neural networks ; Chapter VIII. Modeling and prediction of foreign currency exchange markets ; Chapter IX. Improving returns on stock investment through neural network selection ; Chapter X. Neural networks in manufacturing operations ; Chapter XI. Highr-Pressure Dic-Casting process modeling using neural networks ; Chapter XII. Neural network models for the estimation of product costs: an application in the automative industry ; Chaper XIII. Aneural.network-assisted optimization framework and its use for optimum-parameter identification ; Chapter XIV. Artificial neural network s in manufacturing: sheduling ; XV. Recognition of lubrication defects in cold forging proess with a neural network.

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. Contraportada.