SC Test - 1

Supervised Learning is

• learning with the help of examples
• learning without teacher
• learning with the help of teacher
• learning with computers as supervisor

Artificial Intelligence is different from soft computing in the sense

• Conventional Artificial Intelligence deal with prdicate logic where as soft computing deal with fuzzy logic
• Conventional Artificial Intelligence methods are limited by symbols where as soft computing is based on empirical data
• Both (a) and (b)
• None of the above

The membership functions are generally represented in

• Tabular Form
• Graphical Form
• Mathematical Form
• Logical Form

Artificial neural network used for

• Pattern Recognition
• Classification
• Clustering
• All of these

Three main basic features involved in characterizing membership function are

• Intution, Inference, Rank Ordering
• Fuzzy Algorithm, Neural network, Genetic Algorithm
• Core, Support , Boundary
• Weighted Average, center of Sums, Median

Fuzzy Computing

• doesnt deal with 2 valued logic
• mimics human behaviour
• deals with information which is vague, imprecise, uncertain, ambiguous, inexact, or probabilistic
• All of the above

Ability to learn how to do tasks based on the data given for training or initial experience

• Self Organization
• Adaptive Learning
• Fault tolerance
• Robustness

In artificial Neural Network interconnected processing elements are called

• nodes or neurons
• weights
• axons
• Soma

The _______ of an organism is measured by means of success of organism in life

• Strength
• fitness
• Gene
• Chromosome

A fuzzy set whose membership function has at least one element x in the universe whose membership value is unity is called 

• sub normal fuzzy sets
• normal fuzzy set
• convex fuzzy set
• concave fuzzy set