www.parikshapapers.in. Page 1 of 1. SOFT COMPUTING TECHNIQUE.pdf. SOFT COMPUTING TECHNIQUE.pdf. Open. Extract. Open with
1. a) How does genetic algorithm works? Explain with ... Explain the Classical Newton's Method. 13. ... Displaying SOFT
The last thirty years saw a dramatic rise in popularity of nature-inspired metaheuristics .... Functions 9-12 map five holes of equal width. One of ..... vector is limited within the range [−vmax i,vmax i]. 2 min max max i i i u v. −. ⋅= (5) ... The
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as sentential logic and predicate logic, or rely heavily on the mathematical capabilities ... soft computing are fuzzy logic, ANN theory and probabilistic reasoning, ...
Antonio Di Nola (University of Salerno, Italy). Yun Shang (AMSS, Chinese Academy of Sciences, China). Haizhong Shi (North-West Normal University, China).
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Mar 2, 2000 - Chapter 1 is an introduction to soft computing providing a brief history about its origins and what it may
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... Dept. of CIS & QMST, Southwest Texas State. University, San Marcos, Texas 78666. Joan C. Hubbard, Dept. of Mgmt
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Write in detail about Problem Solving in Genetic Algorithm. 7. Explain in ... Explain in detail about the newton's metho
G5P2/18A16 Reg. No
St. Joseph’s College of Arts & Science (Autonomous) St. Joseph’s College Road, Cuddalore – 607001 PCA1124S - SOFT COMPUTING Time : 3 hrs
Max Marks :75 SECTION – A (5X5=25) Answer ALL the Questions
1. a) Write a short note on genetic operators. (Or) b) How does the genetic algorithms work? 2. a) Where are neural networks being used? (Or) b) Write a short note on competitive networks. 3. a) Write any five Properties of fuzzy measures. (Or) b) Write brief note on set theoretic operations on fuzzy sets. 4. a) Write short note on the method of steepest descent to minimize a given function. (Or) b) Give an account on random search method in derivative free objective function. 5. a) Draw the diagram of color manufacturing intelligence architecture. (Or) b) Write some of the applications of Computational Intelligence.
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G5P2/18A16
SECTION - B (5X10=50) Answer any FIVE Questions 6. Write in detail about Problem Solving in Genetic Algorithm. 7. Explain in detail the neural network architectures and the methods of setting the weights. 8. Enumerate the back propagation in neural networks. 9. Write a detailed note on the applications of fuzzy set theory to different branches of science and technologies. 10. Explain in detail about the newton’s method in derivative based optimization. 11. Describe in detail the downhill simplex search derivative free method for multidimensional function optimization. 12. Write a brief note on automobile MPG prediction problem. 13. Describe in detail the CANFIS modeling for color recipe prediction. ************
