Soft computing is a rapidly becoming popular set of paradigms to seek solution to complex problems and are tolerant of imprecision, uncertainty, partial truth, and approximation. They exploit the tolerance for imprecision, uncertainty, partial truth, approximation and ability to learn from environment to achieve tractability, robustness and low solution cost.

Soft Computing paradigms has tremendous power of generalization and hence can be used to solve the real world problems in various field like biology, medical, biometry, humanity and management science etc. Soft computing is likely to play an important role in science and engineering, but eventually its influence may extend much farther. Soft computing paradigms mainly involve neural network, fuzzy logic, support vector machine, evolutionary computation, genetic algorithm, probabilistic reasoning with possibility of seamless integration of two or more methodologies. The purpose of this special issue is to showcase research and development, the usage of these paradigms in various fields and to make the evolution in this field by fusion of different soft computing methods.

Potential topics may include but not limited to:

1. Artificial Neural Networks
2. Fuzzy Systems
3. Genetic Algorithms and Evaluative Strategies
4. Support Vector Machines
5. Swarm intelligence
6. Probabilistic learning
7. Integration of different soft computing paradigms
8. Pattern Recognition and Computer Vision
9. Data and Knowledge Visualization
10. Soft computing Applications