It is also referred as computational intelligence. It is the use of inexact solutions to computationally hard tasks such as the solution of NP-complete problems, for which there is no known algorithm that can compute an exact solution in polynomial time. Soft computing differs from conventional (hard) computing in that, unlike hard computing, it is tolerant of imprecision, uncertainty, partial truth, and approximation. Components of soft computing include: Machine learning, Neural networks (NN), Perceptron, Support Vector Machines (SVM), Fuzzy logic (FL), Evolutionary computation (EC), including: Evolutionary algorithms, Genetic algorithms, Differential evolution, Metaheuristic and Swarm Intelligence, Ant colony optimization, Particle swarm optimization, Ideas about probability including: Bayesian network.
Related Journals of Soft Computing:
Journal of Global Research in Computer Science, Journal of Computer Science & Systems Biology, Journal of Information Technology & Software Engineering, International Journal of Innovative Research in Computer and Communication Engineering, Computer Engineering & Information Technology, American Journal of Computer Science and Information Technology