SUBJECT: Neural Networks and Soft Computing(NNSC)

Regulation: R20 A.Y.:2025-26

Name of the Faculty: M.SUMAN Year & Sem: IV-I

UNIT-1
Topic name: Introduction of Soft Computing
1. What is soft Computing, Explain in brief.[7] - Understand-Model Question

Topic name: Soft Computing vs. Hard Computing

2. How are soft computing constituents different from conventional AI? Explain. [7]- Understand -Jan-
2024, Set-1
3. Discuss the similarities and differences between soft computing and hard computing[7].-Understand-
Dec-2024, Set-1.

Topic name: Various Types of Soft Computing Techniques

4. Explain the various types of Soft Computing Techniques[14] - Analyze-Model Question
Topic name: Applications of Soft Computing
5. Explain the various Applications of Soft Computing. [7] - Apply-Model Question
Topic name: AI Search Algorithm
6. Discuss various Search algorithms of AI Techniques[14] - Analyze-Model Question
7. What is searching Algorithm give steps involved in problem solving. AI searching Algorithms[7]-
Analyze –Model Question
8. Discuss the following Search Algorithms[7] – Apply-Model Question
i. Breadth first Search Algorithm
ii. Depth first search Algorithm
iii. Uniform search Algorithm
9. How do uninformed (blind) search algorithms differ from informed (heuristic) search algorithms?
Explain.[7] – Analyze- Jan-2024, Set-1
10. Explain A* search with a suitable example-Analyze[7]-Dec-2024, Set-1
Topic name: Predicate Calculus-Rules of Inference
11. Discuss the Predicate Calculus and rules of inference.[14] - Analyze-Model Question
12. How are predicate calculus statements converted into machine-readable representations for AI
algorithms and systems? Explain[7]-Analyze-Dec-2024, Set-1
Topic name: Semantic Networks-Frames & Objects
13. How knowledge is represented in terms of Semantic Networks, discuss in detail using neat
diagrams.[14] - Understand-Model Question
14. How are semantic networks related to the concept of ontologies, and what role do they play in the
semantic web? Explain. [7] –Understand- Jan-2024, Set-1
Topic name: Hybrid Models
15. Briefly discuss the different Hybrid Models of the Soft Computing.[7] - Evaluate-Model
Question
16. How can hybrid models leverage the strengths of different soft computing techniques to solve
complex optimization problems? Explain[7]- Apply- Jan-2024, Set-1

UNIT- 2
Topic name: Introduction to Neuron Model
1. What challenges and limitations are associated with training ANNs? Explain.[7] - Understand-Dec-
2024, Set-1
2. Discuss the MC-Culloch and the Adaline Neron Models[7]-Understand-Model Question
3. What is an artificial neural network (ANN)? How does it draw inspiration from biological neural
networks? Explain.[7]- Understand- Jan-2024, Set-1
Topic name: Neural Network Architecture- Perceptrons, Single Layer Perceptrons, Multilayer
Perceptrons

4. What are the various types of neuron activation functions? Explain with a
neat sketch.[7] - Analyze-Model Question
5. Differentiate between single-layer perceptron and multilayer perceptron with a neat sketch
diagram.Remember-Dec-2024,Set-1
Topic name: Learning Rules
6. Discuss the various learning rules of the Artificial Neural Networks[7] - Understand-Model Question

Topic name: Back propagation Networks

7. Describe the backpropagation algorithm and its role in training feedforward neural networks. [7]
8. - Analysis- Dec-2024,Set-1
9. What are the limitations of Back Propagation algorithm?[7] - Remember-Model Question

Topic name: Kohnen's self organizing networks

10. Discuss the Kohnen's self organizing networks[7] -Analysis-Model Question
Topic name: Hopfield network
11. Discuss the structure and architecture of the Hopfield network. [14] - Analysis- Jan-2024, Set-1
12. Discuss the steps involved in the training of a Hopfield network.[7]-Understand-Dec-2024, Set-1.
Topic name: Applications of NN
13. Discuss the applications of the Artificial Neural Networks[7] - Apply-Model Question
14. How are neural networks used in recommender systems and personalized content delivery? Explain[7]
-Apply -Jan-2024, Set-1

UNIT 3
Part-A
Topic name: Introduction Fuzzy Logic
1. Explain fuzzy versus crisp set operations with an example.[7] - Understand-Model Question
2. What is crisp set? Explain the operations and properties of crisp set.[7] - Understand-Model
Question
3. Explain the following with respect to fuzzy logic. i) Linguistic variables ii) Concentration iii) Dilation
[7]-Understand-Jan-2024, Set-1
4. How does fuzzy logic address uncertainty and vagueness in data and decisionmaking?[7] –Analyze-
Dec-2024, Set-1
Topic name: Fuzzy sets and Fuzzy reasoning
5. Define Fuzzy set? Explain in brief about Member ship function of Fuzzy set?[7] Analyze-
Model Question
6. Define the following with example[7] - Remember-Model Question

i) Membership
ii) Power set
iii) Super set
iv) Cardinality
Topic name: Basic functions on fuzzy sets and relations
7. Define Fuzzy set? Explain in brief about Member ship function of Fuzzy set?[7] - Remember-
Model Question
8. Discuss the four T-norm operators and their significance[7]-Analyze- Jan-2024, Set-1
9. What is Sugeno’s complement? How is it different from Yager’s complement? Explain.[7]-Analyze-
Jan-2024, Set-1
10. Two fuzzy sets defined by A={(x1,0.2) (x2,0.5)(x3,0.6)} and B={(x1,0.1)
(x2,0.4)(x3,0.5)} [7] - Apply-Model Question
Find i) Product of a fuzzy sets
 ii) Intersection
iii) Complement

Part-B
Topic name: Rule based models and linguistic variables
11. Discuss about the rule base and the linguistic Variables[7] - Understand-Model Question
Topic name: Fuzzy controls
12. What is a fuzzy control system, and how does it utilize fuzzy logic for process control? Explain. [7] -
Remember-Dec-2024, Set-1
13. Explain the fuzzy inference system with a block diagram.[7]- Undestand- Jan-2024, Set-1
14. Explain the single-input Tsukamoto fuzzy model with a suitable diagram.[7]- Remember-Dec-2024,
Set-1
Topic name: Fuzzy decision making
15. Discuss the decision making system[7] - Analysis-Model Question
Topic name: Applications of fuzzy logic.
16. Give the applications of the Fuzzy logic system[7] - Apply-Model Question

UNIT 4
Topic name: Introduction to Genetic Algorithm
1. What is the basic principle involved in the operation of Genetic Algorithm[7] - Understand-
Model Question
Topic name: Fitness Computations
2. Explain the role of Fitness Function in generating the population.[7] - Analyze-Model Question
Topic name: Cross Over and Mutation
3. Discuss different types of crossover techniques in a genetic algorithm?[7] - Analysis-Dec-2024,Set-1
4. What do you mean by mutation? Explain[7] - Analysis-Model Question
5. Discuss the practical applications of genetic algorithms in any two domains.[7]-Apply- Jan-2024, Set-
1
6. Define any five termination conditions of the genetic algorithm. [7]- Understand-Jan-2024, Set-1
7. How to solve a problem with more than one optimization criterion? Explain with an example.[7]-
Analyze-. Jan-2024, Set-1
Topic name: Evolutionary Programming and Classifier Systems
8. Explain briefly about evolutionary Programming.[7] - Remember-Model Question
Topic name: Variants and Applications GA
9. Discuss any two variants of the genetic algorithm. [7] - Apply-Dec-2024, Set-1
Topic name: Ant Colony Optimization
10. Explain about the Ant Colony optimization Algorithm[7] - Remember-Model Question
Topic name: Particle Swarm Optimization
11. Explain the principles of particle swarm optimization (PSO) and how particles in a swarm search for
optimal solutions. Write an algorithm to show the same. [7] - Remember-Dec-2024, Set-1
12. What are the advantages of swarm optimization algorithms compared to traditional optimization
techniques? Explain.[7]-Understand- Jan-2024, Set-1
Topic name: Artificial Bee Colony Optimization
13. With neat sketches discuss the Artificial Bee colony Optimization[7] - Remember-Model
Question

UNIT 5
Topic name: Neuro fuzzy hybrid systems
1. How do neuro-fuzzy systems adaptively learn and optimize their parameters for any task? Explain.
[7] - Understand-Dec-2024, Set-1.
2. What is the fundamental concept behind neuro-fuzzy hybrid systems? How do they combine the
strengths of neural networks and fuzzy logic? Explain. [7]-Understand- Jan-2024, Set-1
3. Discuss different types of cooperative neural fuzzy systems.[7]-Analyze- Jan-2024, Set-1
4. Discuss the limitations of the hybrid systems and their possible solutions.[7]-Analyze, Dec-2024, Set-
1
Topic name: Adaptive neuro fuzzy inference systems
5. Explain the adaptive neuro fuzzy inference system[7]- Understand-Model Question
Topic name: Fuzzy backpropagation network
6. Discuss the architecture of Fuzzy backpropagation network[7]- Understand-Model Question
7. Discuss how the fuzzy controllers useful in in parameter variation of the Backpropagation Neural
Network [7]-Apply-Model Question
Topic name: Genetic neuro hybrid system
8. What is the role of genetic algorithm in optimizing the weights and parameters of a backpropagation
neural network? How does this hybridization improve training? Explain. [7] Understand-Dec-2024,
Set-1.
9. Why combine a genetic algorithm with a backpropagation network? What is their individual
limitation? How are such limitations overcome in their combination? Explain. [7]-Apply- Jan-2024,
Set-1
Topic name: Genetic algorithm based backpropagation network
 10. Discuss Genetic algorithm based backpropagation architecture[7] -Understand-Model Question
Topic name: Genetic-fuzzy hybrid systems.
11. Explain the Genetic-fuzzy hybrid systems.[7] -Understand-Model Question
12. Discuss how the gentic algorithm used in the fuzzy logic controller and explain which parameters are
controlled[7]-Apply-Model Question
13. Differentiate between neuro-fuzzy hybrid systems and neuro-genetic hybrid systems.[7]-Analyze-
Jan-2024, Set-1