Question 1 : Which of the following can be used for clustering of data ?

- Single layer perception
- Multilayer perception
- Self organizing map
- Gradient Descent Method.

Question 2 : Which Statements is true regarding Biological neuron?

- A Biological neuron has only one input and only one output.
- A Biological neuron can have only one input but multiple output.
- A Biological neuron can have multiple input and multiple output.
- A Biological neuron can have multiple input but only single output.

Question 3 : Which of the following is not true about Perceptrons ?

- It can classify linearly separable patterns
- It has only one output unit
- It does not have any hidden layer
- It can not classify linearly separable patterns

Question 4 : For Neuron, if w1=2, w2= -1 and input vector X=[0.8 1.2] and desired output d= 1, Determine value of T .

- T= 1
- T= 0
- T= 0.4
- T= -0.3

Question 5 : What are the 2 types of learning?

- Improvised and un-improvised
- Supervised and unsupervised
- Layered and un-layered
- Deterministic and non deterministic

Question 6 : For Perceptron learning, the bias and the threshold are:

- Interchangable
- Non Interchangable
- Conditionally Interchangable
- always equal

Question 7 : The square root of fuzzy set is called _____.

- Dilemma
- Dual
- Concentration
- Root mean square

Question 8 : What is a way of representing individual genes?

- Conversion
- Encoding
- Coding
- Decoding

Question 9 : The method of steepest descent, is popularly known as :

- Gradient method
- Downhill method
- Complex method
- Stochastic method

Question 10 : What was the name of the first model which simulated the working of human brain?

- McCulloch-pitts neuron model
- Marvin Minsky neuron model
- Hopfield model of neuron
- Rosenblatt

Question 11 : How many layers are there in adaptive neuro-fuzzy inference systems (ANFIS) ?

- 3
- 5
- 7
- 4

Question 12 : An input to a fuzzy inference system is a :

- A crisp value
- A constant value
- A fuzzy set
- a linguistic variable

Question 13 : In the neuron, attached to the soma are long irregularly shaped filaments called:

- Dendrites
- Axon
- Synapse
- Cerebellum

Question 14 : Choose the correct optimization technique.

- Evolutionary computing
- Mathematical Modelling
- Cylindrical geometry
- Adaptive calculus

Question 15 : Which of the following transformations on membership functions of fuzzy sets enhances the membership values ?

- Dilation
- Concentration
- Intensification
- Fuzzification

Question 16 : What do you mean by the statement :The genes from the already discovered good individuals are exploited.

- Convergence
- Population diversity
- Scarcity
- Population fitness

Question 17 : From the below mentioned systems, choose the one which is not an hybrid system.

- Neuro fuzzy system
- Fuzzy logic system
- Fuzzy genetic
- Neuro genetic

Question 18 : The number of elements in a set is called its_____.

- Modality
- Associativity
- Cardinality
- Elasticity

Question 19 : The interconnections of a perceptron are :

- Unidirectional
- Bidirectional
- Scatterred
- Linear

Question 20 : Which of the following search techniques has the capacity to overcome the problem of local optima ?

- Genetic algorithms
- Neural Network
- Depth First Search
- Fuzzy Logic

Question 21 : Choose the correct sequence of steps taken in designing a fuzzy logic controller.

- Fuzzification â†’ Rule evaluation â†’ Defuzzification
- Fuzzification â†’ Defuzzification â†’ Rule evaluation
- Rule evaluation â†’ Fuzzification â†’ Defuzzification
- Rule evaluation â†’ Defuzzification â†’ Fuzzification

Question 22 : Which of the following phenomena is not modeled by fuzzy set theory?

- Randomness
- Vagueness
- Uncertainty
- Certainty

Question 23 : Genetic Algorithms are inspired by____.

- Statistical mechanics
- Big bang theory
- Natural evolution
- Deployment theory

Question 24 : The coffee is warm.Here linguist variable warm can be represented by:

- Crisp Logic
- Boolean set theory
- Fuzzy logic
- Real Number

Question 25 : Characteristic features of membership functions are:

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

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