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List and explain any three biologically inspired algorithms/paradigms that simulate natural intelligence, which led to the development of intelligent systems.

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Computational Intelligence paradigms Computational Intelligence is the ability to make a computer to face and solve real-life problems just like a intelligent man do it. It includes Artificial Neural Networks(ANN), Evolutionary Computation(EC), Swarm Intelligence(SI) and Fuzzy Systems(FS). 

A. Artificial Neural Networks (ANN): 

The brain is a complex, nonlinear and parallel computer with ability to perform tasks such as recognise pattern, perception and motor control. ANN is the method of simulate biological neural systems to learn, memorise and generalize like human beings. A human brain cortex consists of 10-500 billion neurons with 60 trillion synapses(a synapse is a structure that permits a neuron to pass electrical)

B. Evolutionary Computation (EC): 

It is the simulation of the natural evolution, i.e. survival of the fittest. In the surrounding, we can see that the stronger must win and others will lose. EC applied for data mining, fault diagnosis, classification, scheduling, etc.

C. Swarm Intelligence (SI): 

Swarm Intelligence is the study of behaviour of colonies or groups of social animals, birds, insects, ants, etc. How they communicate and create and manage their own colonies beautifully.

D. Fuzzy Systems: 

Human beings use common sense while facing a problem, just like human beings fuzzy systems can also use common sense and behave like human beings. Fuzzy systems is used to control gear transmission and raking systems, control lifts, home appliances, controlling trac signals, etc.

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