Soft computing techniques including fuzzy logic have been successfully applied to wireless body area networks (WBANs).
In this paper, web server QoS enhancement solutions based on closed-loop intelligent control strategies, including fuzzy logic, are investigated.
It encompasses several computing fields including fuzzy logic (FL) through the fuzzy if-then rules; neural networks (NN) for learning and adaptation; and genetic algorithms for evolutionary computation.
Also, related work that includes fuzzy logic is presented.
Computational intelligence (CI) is a set of nature-inspired computational methodologies, examples of which include Fuzzy Logic systems, Neural Networks, and Evolutionary Computation.
These represent a combination of emerging, complementary problem-solving technologies that include fuzzy logic, probabilistic reasoning, Bayesian networks, neural networks, and evolutionary or genetic algorithms.
The innovative control techniques are outlined including fuzzy-logic based and Nelder-and-Mead based.
Previous approaches to finding such clusters have included fuzzy logic-based approaches [ 27] (also, see [ 28]), probabilistic approaches [ 29, 30], stochastic approaches [ 31], and consensus clustering [ 32].
This study introduces three new approaches, including a fuzzy logic approach, for dynamic part routing.
By its definition, the soft computing is just known as an integration of a number of fields including the fuzzy logic, the neuro-computing techniques, the evolutionary procedures, the genetic computing and the statistical computing algorithms.
