Soft Computing Methods in Human SciencesSpringer Science & Business Media, 19 авг. 2003 г. - Всего страниц: 272 This book considers Soft Computing methods and their applications in the human sciences. Soft Computing methods - including fuzzy systems, neural networks, evolutionary computing and probabilistic reasoning - are state-of-the-art methods in theory formation and model construction. They mainly stem from the natural sciences, and they have already proved to be powerful in their applications because Soft Computing models, particularly fuzzy system models, are simple and correspond well to the actual world and to human reasoning. Hence, we no longer have to use the complicated mathematical models that have prevailed in this research area. Dozens of books and thousands of articles have been devoted to applications of Soft Computing in the natural sciences, but only a few studies have focused on its applications in the human sciences, such as the social and the behavioral sciences - this despite the fact that these novel methods seem to open a number of inspiring prospects in these disciplines. In quantitative research in the human sciences, typical application areas include statistical models that can be replaced by simpler numerical or linguistic Soft Computing models. In qualitative research, Soft Computing methods can enhance modelling because, instead of having to do manual work, we can use computer simulations with approximate and/or linguistic constituents. |
Содержание
Towards Novel Methods in the Human Sciences | 1 |
Brief Introduction to Fuzzy Set Theory | 14 |
The Approximate Truth about the Degrees of Truth | 49 |
Approximate Reasoning | 63 |
Quantitative Data Examination | 84 |
Soft Computing Models for Complex Systems | 198 |
Towards Soft Computing Applications in Qualitative Research | 237 |
List of Figures | 252 |
270 | |
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according actual world ANOVA Model antecedent apply fuzzy approximate reasoning Based on Table bivalent logic cognitive maps conclusion consider constituents context Control Data conventional correlation crisp degrees of membership Dovetailing fairly true false FMT approach foregoing function fuzzy logic Fuzzy Model fuzzy reasoning Fuzzy Relation fuzzy rule bases Fuzzy Rules fuzzy set theory fuzzy systems Gmean Gmpr granulation Hence human sciences hypothesis Ideal tile imprecise independent variables input interpretation interval level of hunger Linear Regression linguistic values Lotfi Zadeh lung cancer Males mathematical model construction modus tollens neural networks node matrix Non-smoking operations output p-value premisses problems qualitative research quantitative Ratios of Observed reasoning model regression analysis Regression Model Residuals SC methods SC Model Section semantic Sets and Systems simulation Smoking Soft Computing Sorites Paradox statistical Tile Assessment tions training data true counterpart truth value Tuned usually variance vectors Weights of Persons yield young
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Modellierung komplexer Prozesse durch naturanaloge Verfahren: Soft Computing ... Christina Stoica-Klüver,Jürgen Klüver,Jörn Schmidt Недоступно для просмотра - 2008 |