11. Which of the following is true for neural networks?

1. It has a set of nodes and connections
2. A node could be in an excited state or non-excited state
3. Each node computes it’s weighted input
4. All of the above

12. Backpropagation is a learning technique that adjusts weights in the neural network by propagating weight changes

1. Backward from sink to source
2. Forward from source to sink
3. Backward from sink to hidden nodes
4. Forward from source to hidden nodes

13. An auto-associative neural network is:

1. A neural network that contains no loops
2. A neural network that contains feedback
3. A neural network that has only one loop
4. A single layer feed-forward neural network with pre-processing

14. Which one of the following is a blind search

1. Depth-search first
2. Best-first search
3. Depth-first search
4. Best-search-first

Computer Networks MCQ Questions And Answers

15. Chance nodes and decision nodes are represented by _____ and _____ respectively

1. Disks and squares
2. Squares and circles
3. Circles and Triangles
4. Circles and squares

16. The fundamental unit of the neural network is

1. Neuron
2. Brain
3. Nucleus
4. Dendrites

17. How many types of Artificial Neural Networks?

1. 2
2. 3
3. 4
4. 5

18. Slots and facets are used in

1. Rules
2. Frames
3. Semantic Networks
4. All of the above

19. A methodology used to develop behavior-based autonomous agents

1. Descriptors
2. Behavior modeling
3. Behavior engineering
4. Auto engineering

20. Which of the following neural networks uses supervised learning?

(A) Multilayer perceptron
(B) Self-organizing feature map
(C) Hopfield network

1. (A) only
2. (B) only
3. (A) and (C) only
4. (A) and (B) only