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. Presents the applications of soft computing techniques for the business field INDICE: From the contents Ensembles of Classifiers in Arrears Management.-Bicluster Analysis of Currency Exchange Rates.- Predicting the Effects of Alternative Pricing Strategies in an Artificial Society Undergoing Technology Adoption.- An Evolutionary Programming based Knowledge Ensemble Model for Business Risk Identification.- The application of Fuzzy Decision Trees in Company Audit Fee Evaluation: A Sensitivity Analysis.- An Exposition of NCaRBS: Analysis of US Banks and Moody’s Bank Financial Strength Rating.- A Clustering Analysisfor Target Group Identification by Locality in Motor Insurance Industry.- Probabilistic Sales Forecasting for Small and Medium-Size Business Operations.- User Relevance Feedback Analysis in Text Information Retrieval: A Rough Set Approach.- Opportunistic Scheduling and Pricing Strategies for Automated Contracting in Supply Chains.- Soft Computing in Intelligent Tutoring Systems and Educational Assessment.
- ISBN: 978-3-540-79004-4
- Editorial: Springer
- Encuadernacion: Cartoné
- Páginas: 350
- Fecha Publicación: 01/05/2008
- Nº Volúmenes: 1
- Idioma: Inglés