Soft Computing Methods In Human Sciences
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Soft Computing Methods in Human Sciences
Author: Vesa A. Niskanen
language: en
Publisher: Springer Science & Business Media
Release Date: 2003-08-19
An in-depth look at soft computing methods and their applications in the human sciences, such as the social and the behavioral 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. The powerful application areas of these methods in the human sciences are demonstrated, including the replacement of statistical models by simpler numerical or linguistic soft computing models and the use of computer simulations with approximate and linguistic constituents. "Dr. Niskanen's work opens new vistas in application of soft computing, fuzzy logic and fuzzy set theory to the human sciences. This book is likely to be viewed in retrospect as a landmark in its field" (Lotfi A. Zadeh, Berkeley)
Soft Computing Methods in Human Sciences
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.
Soft Computing Methods for System Dependability
Technology in today’s world has continued to develop into multifaceted structures. The performance of computers, specifically, has significantly increased leading to various and complex problems regarding the dependability of these systems. Recently, solutions for these issues have been based on soft computing methods; however, there lacks a considerable amount of research on the applications of these techniques within system dependability. Soft Computing Methods for System Dependability is a collection of innovative research on the applications of these processing techniques for solving problems within the dependability of computer system performance. This book will feature comparative experiences shared by researchers regarding the development of these technological solutions. While highlighting topics including evolutionary computing, chaos theory, and artificial neural networks, this book is ideally designed for researchers, data scientists, computing engineers, industrialists, students, and academicians in the field of computer science.