附註:Includes bibliographical references and index.
Business forecasting with artificial neural networks : an overview / G. Peter Zhang -- Using artificial neural networks to forecast market response / Leonard J. Parsons, Ashutosh Dixit -- Forecasting stock returns with artificial neural networks / Suraphan Thawornwong, David Enke -- Forecasting emerging market indexes with neural networks / Steven Walczak -- Predicting wastewater BOD levels with neural network time series models / David West, Scott Dellana -- Tourism demand forecasting for the tourism industry : a neural network approach / Rob Law, Ray Pine -- Using an extended self-organizing map network to forecast market segment membership / Melody Y. Kiang [and others] -- Back propagation and Kohonen self-organizing feature map in bankruptcy prediction / Kidong Lee, David Booth, Pervaiz Alam -- Predicting consumer situational choice with neural networks / Michael Y. Hu, Murali Shanker, Ming S. Hung -- Forecasting short-term exchange rates : a recurrent neural network approach / Leong-Kwan Li [and others] -- A combined ARIMA and neural network approach for time series forecasting / G. Peter Zhang -- Mehtods for multi-step time series forecasting with neural networks / Douglas M. Kline -- A weighted window approach to neural network time series forecasting / Bradley H. Morantz, Thomas Whalen, G. Peter Zhang -- Assessment of evaluation methods for prediction and classifications of consumer risk in the credit industry / Satish Nargundkar, Jennifer Lewis Priestley.
摘要:Forecasting is one of the most important activities that form the basis for strategic, tactical, and operational decisions in all business organizations. Recently, neural networks have emerged as an important tool for business forecasting. There are considerable interests and applications in forecasting using neural networks. This book provides for researchers and practitioners some recent advances in applying neural networks to business forecasting. A number of case studies demonstrating the innovative or successful applications of neural networks to many areas of business as well as methods to improve neural network forecasting performance are presented.
