Special issue on granular soft computing for pattern recognition and mining

Special issue on granular soft computing for pattern recognition and mining

This issue introduces the state-of-art in granular soft computng for pattern recognition and mining and presents some novel ontributions. Granulation is a computing paradigm, among othrs such as self-reproduction, self-organization, functioning of rain, Darwinian evolution, group behavior, cell membranes, and orphogenesis that are abstracted from natural phenomena. Granlation is inherent in hum...

Guest Editorial: Special Issue on Software for Soft Computing

The term Soft Computing refers to a family of techniques (Fuzzy Logic, Neuro-computing, Probabilistic Reasoning, Evolutionary Computation, etc.) endowed with the ability to work in a cooperative way, taking profit from the main advantages of each other, thus tackling with complex real-world problems really hard to solve otherwise [6]. In the last years, many software tools have been developed f...

Special Issue on Bridging Metaheuristic and Soft Computing

ficient of Determination and Nash-Sutcliffo Coefficient were used for comparing the prediction ability of the developed models. Four input parameters were Body & texture, aroma & flavour, moisture, and free fatty acid. Neurons in two hidden layers varied from 1 to 20. One output parameter was sensory score. Experiments show that Elman model with combination of 4-17-17-1 performed significantly ...

Special Issue on Soft Computing in the Semantic Web

Special issue on hardware implementations of soft computing techniques

Soft computing (SC) techniques, which include methods from fuzzy logic, neural networks, evolutionary computing, and other similar areas, have proven in the last few years how tolerance for imprecision, uncertainty, or approximation can be exploited to achieve tractable, robust, and low cost solutions. Most of SC methods and algorithms have been implemented in software on common computer system...