Perception-based Data Mining and Decision Making in Economics and Finance [electronic resource] / edited by Ildar Batyrshin, Janusz Kacprzyk, Leonid Sheremetov, Lotfi A. Zadeh.Material type: TextLanguage: English Series: Studies in Computational Intelligence: 36Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2007Description: XVI, 367 p. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9783540362470Subject(s): Engineering | Artificial intelligence | Engineering mathematics | Engineering | Appl.Mathematics/Computational Methods of Engineering | Artificial Intelligence (incl. Robotics)Additional physical formats: Printed edition:: No titleDDC classification: 519 LOC classification: TA329-348TA640-643Online resources: Click here to access online
Data Mining -- Towards Human-Consistent Data-Driven Decision Support Systems via Fuzzy Linguistic Data Summaries -- Moving Approximation Transform and Local Trend Associations in Time Series Data Bases -- Perception Based Patterns in Time Series Data Mining -- Perception-Based Functions in Qualitative Forecasting -- Towards Automated Share Investment System -- Estimating Classification Uncertainty of Bayesian Decision Tree Technique on Financial Data -- Invariant Hierarchical Clustering Schemes -- Decision Making -- Fuzzy Components of Cooperative Markets -- Possibilistic–Probabilistic Models and Methods of Portfolio Optimization -- Toward Graded and Nongraded Variants of Stochastic Dominance -- Option Pricing in the Presence of Uncertainty -- Nonstochastic Model-Based Finance Engineering -- Collective Intelligence in Multiagent Systems: Interbank Payment Systems Application -- Fuzzy Models in Credit Risk Analysis.
The primary goal of this book is to present to the scientific and management communities a selection of applications using recent Soft Computing (SC) and Computing with Words and Perceptions (CWP) models and techniques meant to solve some economics and financial problems that are of utmost importance. The book starts with a coverage of data mining tools and techniques that may be of use and significance for economic and financial analyses and applications. Notably, fuzzy and natural language based approaches and solutions for a more human consistent dealing with decision support, time series analysis, forecasting, clustering, etc. are discussed. The second part deals with various decision making models, particularly under probabilistic and fuzzy uncertainty, and their applications in solving a wide array of problems including portfolio optimization, option pricing, financial engineering, risk analysis etc. The selected examples could also serve as a starting point or as an opening out, in the SC and CWP techniques application to a wider range of problems in economics and finance.