<p><span>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, bicl
Soft Computing Applications in Business
β Scribed by Chris Matthews, Esther Scheurmann (auth.), Bhanu Prasad (eds.)
- Publisher
- Springer-Verlag Berlin Heidelberg
- Year
- 2008
- Tongue
- English
- Leaves
- 296
- Series
- Studies in Fuzziness and Soft Computing 230
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
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 Moodyβs 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.
β¦ Table of Contents
Front Matter....Pages -
Ensembles of Classifiers in Arrears Management....Pages 1-18
Bicluster Analysis of Currency Exchange Rates....Pages 19-34
Predicting the Effects of Alternative Pricing Strategies in an Artificial Society Undergoing Technology Adoption....Pages 35-55
An Evolutionary Programming Based Knowledge Ensemble Model for Business Risk Identification....Pages 57-72
The Application of Fuzzy Decision Trees in Company Audit Fee Evaluation: A Sensitivity Analysis....Pages 73-91
An Exposition of NCaRBS: Analysis of US Banks and Moodyβs Bank Financial Strength Rating....Pages 93-111
A Clustering Analysis for Target Group Identification by Locality in Motor Insurance Industry....Pages 113-127
Probabilistic Sales Forecasting for Small and Medium-Size Business Operations....Pages 129-146
User Relevance Feedback Analysis in Text Information Retrieval: A Rough Set Approach....Pages 147-178
Opportunistic Scheduling and Pricing Strategies for Automated Contracting in Supply Chains....Pages 179-199
Soft Computing in Intelligent Tutoring Systems and Educational Assessment....Pages 201-230
A Decision Making System for the Treatment of Dental Caries....Pages 231-242
CBR Based Engine for Business Internal Control....Pages 243-260
An EMD-Based Neural Network Ensemble Learning Model for World Crude Oil Spot Price Forecasting....Pages 261-271
Structured Hidden Markov Models: A General Tool for Modeling Agent Behaviors....Pages 273-292
Back Matter....Pages -
β¦ Subjects
Appl.Mathematics/Computational Methods of Engineering; Artificial Intelligence (incl. Robotics)
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