Soft computing is an association of computing methodologies that includes fuzzy logic, neuro-computing, evolutionary computing, and probabilistic computing. After a brief overview of Soft Computing components, we will analyze some of its most synergistic combinations. We will emphasize the development of smart algorithm-controllers, such as the use of fuzzy logic to control the parameters of ev...

bearing capacity prediction of shallow foundation is one of the most important problems in geotechnical engineering practices, with a wide variety range of methods which have been introduced to forecast it accurately. recently, soft computing methods such as artificial neural networks (anns) and support vector machines (svms) have been used for prediction of the ultimate bearing capacity of sha...

Soft computing techniques are becoming popular in designing real world applications. Researchers are trying to integrate different soft computing paradigms such as fuzzy logic, artificial neural network, genetic algorithms, decision trees etc. to develop hybrid intelligent autonomous classification systems that provide more flexibility by exploiting tolerance and uncertainty of real life situat...

In this paper, a new soft computing group decision method based on the concept of compromise ratio is introduced for determining decision makers (DMs)' weights through the group decision process under uncertainty. In this method, preferences and judgments of the DMs or experts are expressed by linguistic terms for rating the industrial alternatives among selected criteria as well as the relativ...

Soft computing methods such as fuzzy control, neural networks, etc., often require lots of computations even for small amounts of data. It is, therefore, sometimes believed that for larger amounts of data, the required amount of computations will be so large that we will reach the frontiers of soft computing. In this paper, we show, on the example of hyperspectral satellite imaging, that this b...