Soft Computing MCQ
Question 1 : Which of the following can be used for clustering of data ?
- Single layer perception
- Multilayer perception
- Self organizing map
- Gradient Descent Method.
Question 2 : Which Statements is true regarding Biological neuron?
- A Biological neuron has only one input and only one output.
- A Biological neuron can have only one input but multiple output.
- A Biological neuron can have multiple input and multiple output.
- A Biological neuron can have multiple input but only single output.
Question 3 : Which of the following is not true about Perceptrons ?
- It can classify linearly separable patterns
- It has only one output unit
- It does not have any hidden layer
- It can not classify linearly separable patterns
Question 4 : For Neuron, if w1=2, w2= -1 and input vector X=[0.8 1.2] and desired output d= 1, Determine value of T .
- T= 1
- T= 0
- T= 0.4
- T= -0.3
Question 5 : What are the 2 types of learning?
- Improvised and un-improvised
- Supervised and unsupervised
- Layered and un-layered
- Deterministic and non deterministic
Question 6 : For Perceptron learning, the bias and the threshold are:
- Non Interchangable
- Conditionally Interchangable
- always equal
Question 7 : The square root of fuzzy set is called _____.
- Root mean square
Question 8 : What is a way of representing individual genes?
Question 9 : The method of steepest descent, is popularly known as :
- Gradient method
- Downhill method
- Complex method
- Stochastic method
Question 10 : What was the name of the first model which simulated the working of human brain?
- McCulloch-pitts neuron model
- Marvin Minsky neuron model
- Hopfield model of neuron
Question 11 : How many layers are there in adaptive neuro-fuzzy inference systems (ANFIS) ?
Question 12 : An input to a fuzzy inference system is a :
- A crisp value
- A constant value
- A fuzzy set
- a linguistic variable
Question 13 : In the neuron, attached to the soma are long irregularly shaped filaments called:
Question 14 : Choose the correct optimization technique.
- Evolutionary computing
- Mathematical Modelling
- Cylindrical geometry
- Adaptive calculus
Question 15 : Which of the following transformations on membership functions of fuzzy sets enhances the membership values ?
Question 16 : What do you mean by the statement :The genes from the already discovered good individuals are exploited.
- Population diversity
- Population fitness
Question 17 : From the below mentioned systems, choose the one which is not an hybrid system.
- Neuro fuzzy system
- Fuzzy logic system
- Fuzzy genetic
- Neuro genetic
Question 18 : The number of elements in a set is called its_____.
Question 19 : The interconnections of a perceptron are :
Question 20 : Which of the following search techniques has the capacity to overcome the problem of local optima ?
- Genetic algorithms
- Neural Network
- Depth First Search
- Fuzzy Logic
Question 21 : Choose the correct sequence of steps taken in designing a fuzzy logic controller.
- Fuzzification → Rule evaluation → Defuzzification
- Fuzzification → Defuzzification → Rule evaluation
- Rule evaluation → Fuzzification → Defuzzification
- Rule evaluation → Defuzzification → Fuzzification
Question 22 : Which of the following phenomena is not modeled by fuzzy set theory?
Question 23 : Genetic Algorithms are inspired by____.
- Statistical mechanics
- Big bang theory
- Natural evolution
- Deployment theory
Question 24 : The coffee is warm.Here linguist variable warm can be represented by:
- Crisp Logic
- Boolean set theory
- Fuzzy logic
- Real Number
Question 25 : Characteristic features of membership functions are:
- Intution, Inference, Rank Ordering
- Fuzzy Algorithm, Neural network, Genetic Algorithm
- Core, Support , Boundary
- Weighted Average, center of Sums, Median