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Cloud computing and Soft Computing

Clouding computing is emerging as a powerful new computing revolution, which many predict well not only reshape business, society and culture in a profound way, but also provide an electrifying impact on the way how we do research and education in science and engineering. It is the most recent evolution of distributed and scalable computing that uses internet-based ("cloud") computing. As described in Wikipedia, 'It is a style of computing in which IT-related capabilities are provided "as a service," allowing users to access technology-enabled services from the Internet ("in the cloud") without knowledge of, expertise with, or control over the technology infrastructure that supports them." It incorporates a number of recent Web-based computing trends such as software as a service and Web2.0, and is quickly replacing cluster and grid computing that has been the preferred method of meeting needs for high end computing such as what is needed for many scientific computing applications.

A Definition of Soft Computing - adapted from L.A. Zadeh

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What Is Soft Computing?

Soft computing differs from conventional (hard) computing in that, unlike hard computing, it is tolerant of imprecision, uncertainty, partial truth, and approximation. In effect, the role model for soft computing is the human mind. The guiding principle of soft computing is: Exploit the tolerance for imprecision, uncertainty, partial truth, and approximation to achieve tractability, robustness and low solution cost. The basic ideas underlying soft computing in its current incarnation have links to many earlier influences, among them Zadeh's 1965 paper on fuzzy sets; the 1973 paper on the analysis of complex systems and decision processes; and the 1979 report (1981 paper) on possibility theory and soft data analysis. The inclusion of neural computing and genetic computing in soft computing came at a later point.

Soft computing techniques

Artificial neural networks (ANN) are data modelling tools that are increasingly used in civil and geotechnical engineering because of their ability to model complex relationships between inputs and outputs without a theoretical model.

The aim of this project was to study the capability of ANN to simulate the output of a problem where it was possible to compare the results with an existing numerical model. The undrained capacity T-max of suction anchors in soft clay was chosen as a suitable problem.

Soft Computing

What is Soft Computing?

Introduction
The concept of fuzzy set was introduced by Zadeh in 1965 to allow elements to belong to a set in a gradual rather than an abrupt way (i.e. permitting memberships valued in the interval [0,1] instead of in the set {0,1}). Ever since then, applications and developments based on this simple concept have evolved to such an extent that it is practically impossible nowadays to encounter any area or problem where applications, developments, products, etc. are not based on fuzzy sets.