AKTU · B.Tech · Important questions
AKTU Introduction to Soft Computing Important Questions
The questions AKTU asks again and again in Introduction to Soft Computing, found by comparing every question in 6 previous year papers from 2016-17 to 2022-23 (subject codes EOE041, KOE036, KOE046, NOE041).
How this list is made: we compared all 142 questions in these papers and grouped the ones that ask about the same thing. Each item shows how many papers it appeared in, which years, and other ways it was worded. Topics that come back often are a strong hint, not a guarantee, so study your full syllabus too.
Most repeated long questions
From Sections B and C (7 or 10 marks, depending on the year). Unit numbers come from Section C, where each question covers one unit.
- Define an artificial neural network. State the characteristics of an artificial neural network.
- Describe artificial neural network multilayer perceptron model.
- Explain important characteristics and applications of artificial neural network.
- Discuss the factors affecting the training of back propagation neural network.
- Discuss the role of back propagation in training a neural network?
- Explain the different types of Operation used in Fuzzy Set with suitable examples
- Use GA to solve the following non-linear programming problem: Minimize (x - 2.5) + (y - 5) subject to 5.5x + 2y - 18 ≤ 0, 0≤x, y≥5.
- Define fuzzy Automata in brief.
- Explain the fuzzy languages and how it is processed in fuzzy automata.
- Differentiate between Roulette-wheel based on fitness and Roulette wheel based on ran with suitable example
- Discuss the selection of Various parameter in BPN.
- Explain Travelling salesman Problem using genetic problem with example.
- Propose a solution to travelling salesman problem using genetic algorithm.
- Explain in brief Fuzzification and Defuzzification.
- Illustrate various defuzzification methods in details.
- Explain the Greg Voit’s Fuzzy Cruise Controller
- Explain the Hopfield network with an example.
- Discuss Hopfield network store and retrieve information with suitable example.
- Explain the following Neural Network Architecture in Details: (i) Rosenblatt’s Perceptron Model (ii) McCulloch- Pitts Model
- Find the weights required to perform the following classification using perceptron network. The vectors (1,1,1,1) and (-1,1-1,-1) are belonging to the class (so have target 1), vectors (1,1,1,-1) and (1,-1,-1,1) are not belonging to the class (so have target value -1). Assume learning rate is 1 and weights is 0.
- What are different attributes of predicate logic? Using inference in predicate logic prove following statement (i) All men are mortal (ii) Socrates is a man Prove: Socrates is mortal
- What is Genetic Algorithm? Draw the general flow diagram of genetic algorithm.
Most repeated short questions (2 marks)
From Section A. Learn a crisp definition plus one example or line of explanation for each.
- Artificial Intelligence can be used in Neural Network or not. Justify your answer.
- Define the fuzzy inference.
- Use the Hebb rule to store the vector [1 1 1 -1] in an auto-associative neural network
- What do you mean by convergence of GA?
- What is FLC?
- What is Reinforcement Learning?
- What is Soft Computing?
- What is soft computing? What distinguishes it from traditional computing?
- What is the Mutation?
- What is the significance of fuzzy Quantifier?
- Why single layer perceptron is used?
- How does a multilayer perceptron differ from a single-layer perceptron?
- Write different applications of neural networks.
- Write the benefit of GA.
Unit-wise questions from recent papers
Section C questions from the latest papers (2022-23 KOE046, 2022-23 KOE036, 2021-22 KOE046), sorted by unit. Use these to practise one unit at a time.
Unit 1
- Construct KSOM to cluster 3 given vectors [1,0,1],[1,1,1],[1,0,1] and number of clusters to be formed is 2.Assume an initial learning Rate of 0.7. (2022-23, KOE036)
- Solve A Back propagation Neural Network with two given inputs X1, X2= [0.09,0.10] and Weights which are connected to Hidden Layer H1 are[0.17,0.22] and Weights which are connected to Hidden Layer H2 are [0.27,0.32] with Bias b1=0.38. Weights which are connected to output Layer O1 are [0.42,0.47] and Weights which are connected to Output Layer O2 are [0.52,0.57] with Bias b2=0.64 and Desired outputs are O1, O2= [0.01,0.97]. Solve it with At least 1 Iteration, Assume the Learning rate is 1. (2022-23, KOE036)
- Explain the process of learning in Kohnen’s self organizing network with suitable example. (2022-23, KOE046)
- Discuss Hopfield network store and retrieve information with suitable example. (2022-23, KOE046)
- Explain the Hopfield network with an example. (2021-22, KOE046)
- Discuss about the supervised learning strategy. (2021-22, KOE046)
Unit 2
- Write a short note on the following (i) Rank space method (ii) Genetic algorithm based Internet search techniques. (2022-23, KOE036)
- Explain the terms Fuzzy Control, Neuro Fuzzy Control and Hybrid Fuzzy Control. (2022-23, KOE036)
- Explain the fuzzy languages and how it is processed in fuzzy automata. (2022-23, KOE046)
- Discuss the handling of uncertainty in inputs and outputs using fuzzy functions. (2022-23, KOE046)
- Give reasons for using fuzzy logic in AI. List a few examples from the world of industry where fuzzy logic is utilized for control. (2021-22, KOE046)
- Let X = {a, b, c, d} Y={1,2,3,4} And the three fuzzy sets be given as: Calculate the implication relation i IF x is Fuzzy set A THEN y is Fuzzy set B ii IF x is Fuzzy set A THEN y is Fuzzy set B ELSE y is Fuzzy set C. (2021-22, KOE046)
Unit 3
- What do you mean by Genetic Algorithm? Explain it with all phases and also draw flow chart. (2022-23, KOE036)
- What is MATLAB? Also Explain modules of MATLAB System. (2022-23, KOE036)
- Discuss the method of grouping similar data points together using clustering algorithms. (2022-23, KOE046)
- How does simulated annealing work as an optimization technique? (2022-23, KOE046)
- Two fuzzy sets I and F are defined as: I = {(F,0.4), (E,0.3), (X,0.1), (Y,0.1), (I,0.9), (T,0.8)} F = {(F,0.99), (E,0.8), (X,0.1), (Y,0.2), (I,0.5), (T,0.5)} Determine the following: i.) Fuzzy set I – Fuzzy set F ii.) Verify (De Morgan’s Law) following: Complement of (Fuzzy (2021-22, KOE046)
- Illustrate various defuzzification methods in details. (2021-22, KOE046)
Unit 4
- Explain the term Rule base Structure Identification and Simulated Annealing. (2022-23, KOE036)
- Explain Adaptive Network based Fuzzy Interface System with Mamdani Model. (2022-23, KOE036)
- What role does fitness computation play in the evolutionary process? (2022-23, KOE046)
- How does the rank space method utilize the concept of rank to guide the search process? (2022-23, KOE046)
- Explain rank selection and Roulette wheel selection methods. (2021-22, KOE046)
- What exactly do genetic bitwise operators do? Explain. (2021-22, KOE046)
Unit 5
- Explain in brief Fuzzification and Defuzzification. (2022-23, KOE036)
- What is supervised learning and Unsupervised Learning? Explain both with Diagrams and Examples. (2022-23, KOE036)
- How does a genetic algorithm solve the TSP? (2022-23, KOE046)
- How does the genetic algorithm approach is different from the traditional search techniques? (2022-23, KOE046)
- Propose a solution to travelling salesman problem using genetic algorithm. (2021-22, KOE046)
- What two requirements should a problem satisfy in order to be suitable for solving it by a GA? (2021-22, KOE046)
Papers used for this list
- AKTU Introduction to Soft Computing (KOE036) question paper 2022-23
- AKTU Introduction to Soft Computing (KOE046) question paper 2022-23
- AKTU Introduction to Soft Computing (KOE036) question paper 2021-22
- AKTU Introduction to Soft Computing (KOE046) question paper 2021-22
- AKTU Introduction to Soft Computing (EOE041) question paper 2016-17
- AKTU Introduction to Soft Computing (NOE041) question paper 2016-17
How to use these questions
- Start with the questions asked in the most papers, and make short notes for each.
- Write 2–3 long answers by hand with a timer (about 12–15 minutes each), then compare them with your textbook.
- Revise all the 2-mark questions the night before the exam.
- Finish with one full paper from the list above, timed.
Full plan with AI prompts: How to prepare for AKTU exams using previous year papers. After results, check your marks with the AKTU CGPA calculator.
Frequently asked questions
Are these AKTU Introduction to Soft Computing questions guaranteed to come in the exam?
No. They are the questions that repeated most in past papers, which makes them a strong hint, but AKTU can ask anything from the syllabus. Use this list to prioritise, not to skip units.
How was this important questions list made?
We compared all 142 questions from 6 AKTU Introduction to Soft Computing papers (2016-17 to 2022-23) and grouped questions that ask about the same topic, then counted how many papers each appeared in.
Where can I download AKTU Introduction to Soft Computing previous year papers?
Every paper used here is on LearnAIFast with all questions as text and a link to the original PDF. See the list of papers above.
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