Business applications of neural networks : the state-of-the-art of real-world applications

Title:

Series:

Progress in neural processing ; 13

Publication Information:

Singapore : World Scientific Publishing Company, 2000

ISBN:

9789810240899

Subject Term:

Artificial neural networks

Information storage and retrieval systems -- Business

Added Author:

Lisboa, P. J. G. (Paulo J. G.), 1958-

Edisbury, Bill

Vellido, Alfredo

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Library	Item Barcode	Call Number	Material Type	Item Category 1	Status
Searching... PSZ JB	30000010129313	QA76.87 B87 2000	Open Access Book	Book	Searching... Unknown

Neural networks are increasingly being used in real-world business applications and, in some cases, such as fraud detection, they have already become the method of choice. Their use for risk assessment is also growing and they have been employed to visualise complex databases for marketing segmentation. This boom in applications covers a wide range of business interests -- from finance management, through forecasting, to production. The combination of statistical, neural and fuzzy methods now enables direct quantitative studies to be carried out without the need for rocket-science expertise.This book reviews the state-of-the-art in current applications of neural-network methods in three important areas of business analysis. It includes a tutorial chapter to introduce new users to the potential and pitfalls of this new technology.

P. J. G. Lisboa and A. VellidoS. CummingsR. Setiono and J. Y. L. Thong and C.-S. YapA. Vellido and P. J. G. Lisboa and K. MeehanA. H. Boussabaine and M. WanousK. Kiviluoto and P. Bergius and J. MaaranenM. Somers and G. PiperI. SandhuJ. Shawe-Taylor and K. Howker and P. Gosset and M. Hyland and H. Verrelst and Y. Moreau and C. Stoermann and P. BurgeK. HassibiB. Chartier and T. SpillaneB. Edisbury and R. England and S. Hanson

Preface: Business Applications of Neural Networks	p. vii
1 On the Use of Neural Networks for Analysing Travel Preference Data	p. 1
2 Extracting Rules Concerning Market Segmentation from Artificial Neural Networks	p. 13
3 Characterising and Segmenting the Business-to-Consumer E-Commerce Market Using Neural Networks	p. 29
4 A Neurofuzzy Model for Predicting Business Bankruptcy	p. 55
5 Neural Networks for Analysis of Financial Statements	p. 73
6 Developments in Accurate Consumer Risk Assessment Technology	p. 85
7 Strategies for Exploiting Neural Networks in Retail Finance	p. 99
8 Novel Techniques for Profiling and Fraud Detection in Mobile Telecommunications	p. 113
9 Detecting Payment Card Fraud with Neural Networks	p. 141
10 Money Laundering Detection with a Neural-Network	p. 159
11 Utilising Fuzzy Logic and Neurofuzzy for Business Advantage	p. 173
Index	p. 195

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