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Soft Computing Applications in Business 2008 Edition
Contributor(s): Prasad, Bhanu (Editor)
ISBN: 3540790047     ISBN-13: 9783540790044
Publisher: Springer
OUR PRICE:   $161.49  
Product Type: Hardcover - Other Formats
Published: April 2008
Qty:
Additional Information
BISAC Categories:
- Mathematics | Applied
- Computers | Intelligence (ai) & Semantics
- Technology & Engineering | Engineering (general)
Dewey: 006.3
LCCN: 2008923576
Series: Studies in Fuzziness and Soft Computing
Physical Information: 0.69" H x 6.14" W x 9.21" (1.33 lbs) 293 pages
 
Descriptions, Reviews, Etc.
Publisher Description:

Soft computing techniques are widely used in most businesses. This book consists of several important papers on the applications of soft computing techniques for the business field. The soft computing techniques used in this book include (or very closely related to): Bayesian networks, biclustering methods, case-based reasoning, data mining, Dempster-Shafer theory, ensemble learning, evolutionary programming, fuzzy decision trees, hidden Markov models, intelligent agents, k-means clustering, maximum likelihood Hebbian learning, neural networks, opportunistic scheduling, probability distributions combined with Monte Carlo methods, rough sets, self organizing maps, support vector machines, uncertain reasoning, other statistical and machine learning techniques, and combinations of these techniques.

The businesses or business problems addressed in this book include (or very closely related to): analysis of correlations between currency exchange rates, analysis of USA banks and Moody's bank financial strength rating, arrears management, business risk identification, company audit fee evaluation, dental treatments, business internal control, intelligent tutoring systems and educational assessment, modeling agent behavior, motor insurance industry, personal loan defaults, pricing strategies for increasing the market share, pricing strategies in supply chain management, probabilistic sales forecasting, user relevance feedback analysis for online text retrieval, and world crude oil spot price forecasting.