Advanced Neural Network And Fuzzy System Set 1
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This set of Advanced Neural Network and Fuzzy System Multiple Choice Questions & Answers (MCQs) focuses on Advanced Neural Network And Fuzzy System Set 1
Q1 | Fuzzy logic is a form of
- two-valued logic
- crisp set logic
- many-valued logic
- binary set logic
Q2 | The truth values of traditional set theory is ____________ and that of fuzzy set is __________
- either 0 or 1, between 0 & 1
- between 0 & 1, either 0 or 1
- between 0 & 1, between 0 & 1
- either 0 or 1, either 0 or 1
Q3 | How many types of random variables are available?
- 1
- 2
- 3
- 4
Q4 | The values of the set membership is represented by
- discrete set
- degree of truth
- probabilities
- both b & c
Q5 | What is meant by probability density function?
- probability distributions
- continuous variable
- discrete variable
- probability distributions for continuous variables
Q6 | Which of the following is used for probability theory sentences?
- conditional logic
- logic
- extension of propositional logic
- none of the mentioned
Q7 | Fuzzy Set theory defines fuzzy operators. Choose the fuzzy operators from the following.
- and
- or
- not
- ex-or
Q8 | There are also other operators, more linguistic in nature, called __________ that can be applied to fuzzy set theory.
- hedges
- lingual variable
- fuzz variable
- none of the mentioned
Q9 | Where does the Bayes rule can be used?
- solving queries
- increasing complexity
- decreasing complexity
- answering probabilistic query
Q10 | What does the Bayesian network provides?
- complete description of the domain
- partial description of the domain
- complete description of the problem
- none of the mentioned
Q11 | Fuzzy logic is usually represented as
- if-then-else rules
- if-then rules
- both a & b
- none of the mentioned
Q12 | ______________ is/are the way/s to represent uncertainty.
- fuzzy logic
- probability
- entropy
- all of the mentioned
Q13 | ____________ are algorithms that learn from their more complex environments (hence eco) to generalize, approximate and simplify solution logic.
- fuzzy relational db
- ecorithms
- fuzzy set
- none of the mentioned
Q14 | Which condition is used to influence a variable directly by all the others?
- partially connected
- fully connected
- local connected
- none of the mentioned
Q15 | What is the consequence between a node and its predecessors while creating Bayesian network?
- conditionally dependent
- dependent
- conditionally independent
- both a & b
Q16 | How many terms are required for building a Bayesian model?
- 1
- 2
- 3
- 4
Q17 | What is needed to make probabilistic systems feasible in the world?
- reliability
- crucial robustness
- feasibility
- none of the mentioned
Q18 | How the entries in the full joint probability distribution can be calculated?
- using variables
- using information
- both a & b
- none of the mentioned
Q19 | How the Bayesian network can be used to answer any query?
- full distribution
- joint distribution
- partial distribution
- all of the mentioned
Q20 | How the compactness of the Bayesian network can be described?
- locally structured
- fully structured
- partial structure
- all of the mentioned
Q21 | To which does the local structure is associated?
- hybrid
- dependent
- linear
- none of the mentioned
Q22 | The primary interactive method of communication used by humans is:
- reading
- writing
- speaking
- all of the mentioned
Q23 | Elementary linguistic units which are smaller than words are:
- allophones
- phonemes
- syllables
- all of the mentioned
Q24 | In LISP, the atom that stands for “true” is
- t
- ml
- y
- time
Q25 | A mouse device may be:
- electro-chemical
- mechanical
- optical
- both b and c