Engineering BE Computer Engineering Sem 7 December 2019 2019 Soft Computing Elective IICBSGS Question Paper - Mumbai University | munotes
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2019 - Product Life Cycle Management PLM CMPNInstitute Level Optional Course IChoice Base
Semester-end · December 2019
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Questions asked in this paper
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Q2 (a) What is Multi-Layer Perceptron? With the Block Diagram explain the algorithm used to adjust weights at each layer. Show it for two layers 10 marks
- (b) Use perceptron learning rule for computing weights after one iteration for the. 10 1 0 0.5]. The learning constant is given by c=0.1. Desired output for
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Q3 (a) Design a Fuzzy system to predict price of the Resale cars. Assume Total Mileage and year of Manufacturing as input variables (attributes) and Sale price as an output variable. Assume 3 descriptors (values of variables) for each input attributes and 5 descriptors for output attributes 1.Show clearly the units used for & universe of discourse of each attribute. 02 2.Create Fuzzy Rulebase for Price prediction Problem. 03 3.Define fuzzy membership functions for all Input and Output attributes
- (b) Kohanan’s Self Organizing Map w.r.t its architecture, Layers, How to 10 determine no. of neurons in the layers (may give example), Neighborhood, Stopping conditions and applications and High 3. Mediumor High 4. (Alpha level) 5. NOT
- (b) Design Mc- Culloch-Pitt’s Neuron model to solve following functions 10
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Q5 (a) Explain Centre of Sums defuzzification techniques with suitable example. 4 marks
- (b) Determine the weights after two iterations for Hebbian learning single 08 neuron network using Bipolar Binary activation function starting with initial and input patterns are = [1.3,-1], X2 =[2.1,3.2], X3 = [-1.2,-1.8] 1
- (c) Describe Roulette wheel and Tournament selection methods in Genetic 08
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Q6 (a) Differentiate Winner Take All and Learning Vector Quantization in terms of
- (b) Why we need Hybrid systems? Draw and explain architecture of ANFIS. 10
- (c) State the differences between derivative based and derivative free 06
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