M.C.A-M.C.A 5th Sem Neural Networks and Fuzzy logic (Elective-II)(University of Pune, Pune-2013)

 

                Fifth Semester M.C.A Examination, May 2013

                   Neural Networks and Fuzzy logic (Elective-II)

                                     (Semester - V)

                             (2008 Pattern) (710905) 

                        MAY-2013        EXAMINATIONS 

 

 

 

Time: 3 Hours                                                Max. Marks : 70 

 

 

Instructions to the candidates: 

 

1) Answer 3 questions from Section – I and Section - II. 

 

2) Answers to the two sections should be written in separate answer books. 

 

3) Neat diagrams must be drawn wherever necessary. 

 

4) Assume Suitable data if necessary. 

 

 

 

 SECTION-I 

 

Q1) a) Explain with neat diagram biological neural network. Compare its performance with artificial Neural Network. [6] 

 

b) What is clustering and what are different methods of clustering? Discuss winner  takes all learning network. [6] 

 

OR 

 

Q2) a) Using MC-Cullochpitts model implement the following logic functions. [6]

i) Ex-OR gate. 

ii) Ex-NOR gate. 

iii) AND gate. 

iv) NAND gate.  

 

b) Compare supervised learning with unsupervised learning. Give suitable example to explain.  [6] 

 

Q3) How weights are adjusted with sigmoid activation function? Explain with example. [12] 

 

OR 

 

Q4) a) Write a short note on  [6]

i) Linearly Non-separable classification problem. 

ii) Hebbs rule  

 

b) Explain how the delta rule is used to adjust the weights of Adaline network. [6] 

 

Q5) a) What is backpropagation? With a schematic two-layer feed forward neural net-work, derive its learning algorithm. [5] 

 

b) Draw a 3-Layer Feed Forward Neural Net Architecture. How we decide the number of neuron in the input and output layer for a particular application? [6] 

 

OR 

 

Q6) a) Explain the architecture and training algorithm used in Hopfield network. [6] 

 

b) What are the applications of back-propogation algorithm? [5] 

 

 

SECTION -II 

 

Q7) Explain the properties of Commutativity, Associativity, Distributivity, Idempotence, Identity with respect to crisp sets.  [12]

 

OR 

 

Q8) Write short notes on [12]

i) Adaptive fuzzy system 

ii) Knowledge base 

iii) Decision making logic in fuzzy logic control systems.  

 

Q9) a) Define defuzzication. Explain different methods of defuzzication. [6] 

 

b) What are the rules based format used to represent the fuzzy information? [6] 

 

OR 

 

Q10) a) Given X={x1,x2,x3,x4} of four varieties of paddy plants, D={d1,d2,d3,d4} of the various diseases affecting the plants and Y={y1,y2,y3,y4} be the common symptoms of diseases. Find SUP-MIN composition.  [6] 

 

b) Discuss in brief how fuzzy rule based model is used for function approximation. [6] 

 

 

Q11) a) Explain theory of approximate reasoning. [5]

 

 b) What are fuzzy implications? Discuss criteria for fuzzy implications. [6] 

 

OR 

 

Q12) a) Write about conditional fuzzy proposition and unconditional fuzzy proposition. [5] 

 

b) What are fuzzy modifiers? Explain with an example.  [6]

Earning:  ₹ 8.10/-