Example Let us consider a fuzzy system with two inputs x₁and x2 (antecedents) and a single output y (consequent).Inputs x and x₂ have three linguistic variables small, mediumand big with a triangular membership function. Output y hastwo linguistic variables small and big with a triangularmembership function as shown in Figure below. The rulebase consists of the following two rules:Rule 1: IF x is small AND xz is medium THEN y is bigRule 2: IF xis medium AND x2 is big THEN y is smallDemonstrate entire process of fuzzification, aggregation anddefuzzification in a fuzzy system and find the output whenthe inputs X₁ and x₂ equal 3.89 and 5.58, respectively.X1(a)x₁= 3.89smallAmedium91min[μ (x₁), M (x₂)]ANDANDbigX2Amedium Rule 1miniARU9Rule 2minX2=5.58Aggregation of Mig (y) and smallbigsmall(b)y(c)smallbig

The type-1 but also type-2 soft numbers: MFs are used to characterize all fuzzy sets. This double MF…

Example Let us consider a fuzzy system with two inputs x₁ and x2 (antecedents) and a single output y (consequent). Inputs x and x₂ have three linguistic variables small, medium and big with a triangular membership function. Output y has two linguistic variables small and big with a triangular membership function as shown in Figure below. The rule base consists of the following two rules: Rule 1: IF x is small AND x.is medium THEN y is big Rule 2: IF x is medium AND x.is big THEN y is small Demonstrate entire process of fuzzification, aggregation and defuzzification in a fuzzy system and find the output when the inputs x₁and x₂ equal 3.89 and 5.58, respectively. XI small Amedium Amedium Rule 1 min Rule 2 min Aggregation of Mig (v) and small (v) x= 3.89 AND AND big 1 minu (x₁)(x₂)] xy=5.58 big small y (c) small big 7

Example Let us consider a fuzzy system with two inputs x₁ and x2 (antecedents) and a single output y (consequent). Inputs x and x₂ have three linguistic variables small, medium and big with a triangular membership function. Output y has two linguistic variables small and big with a triangular membership function as shown in Figure below. The rule base consists of the following two rules: Rule 1: IF x is small AND x.is medium THEN y is big Rule 2: IF x is medium AND x.is big THEN y is small Demonstrate entire process of fuzzification, aggregation and defuzzification in a fuzzy system and find the output when the inputs x₁and x₂ equal 3.89 and 5.58, respectively. XI small Amedium Amedium Rule 1 min Rule 2 min Aggregation of Mig (v) and small (v) x= 3.89 AND AND big 1 minu (x₁)(x₂)] xy=5.58 big small y (c) small big 7

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

See similar textbooks

Related questions

Q: 9. Vikings always tell the truth and Saxons always lie. Given the following information, use a truth…

A: Given statements are: Person A: "I am Viking or B is a Saxon" Person B: "A is a Saxon if C is a…

Q: A Student 1 2 Jack Smith 3 Rina Lowan 4 Louise Rank 5 Charlotte Drew 6 Caitlynn Marsh 7 Laura Budden…

A: In Excel, the "IF" function is used to perform conditional calculations based on a specified…

Q: which of the following describes a three-way interaction?

A: The correct answer is C Explanation ------------------------------------------ A three way…

Q: Write a Java program to simulate the behaviour of a model-based agent for a vacuum cleaner…

A: Define a function named modelBasedAgent that takes the following parameters:char current_location:…

Q: What do you do if you have a low or moderate-risk device with no identifiable predicate device?

A: A predicate may be a word group made up of a main verb and any helping verbs.

Q: A group of international experts in fuzzy set theory were invited to classify the overall…

A: The objective of the question is to design a fuzzy inference system to classify the overall…

Q: If all parameters need to be optimized, which of the models can use Goal Seek to optimize? a.…

A: In Excel software, Goal Seek is used to determine the value of cell that is used as input in the…

Q: Show that the fuzzy rule "If x is A OR y is B then z is C" is equivalent to the union of the two…

A: Let A be x is A, C be Z is C and B be y is B. The statement 'If y is B then z is C' can be written…

Q: Describe how these statements diffffer, in terms of who receives a balloon and under what

A: For statement 01, domain x and domain g is applied to both A(x, g) and B(x) For all students x,…

Q: Consider the following inference chaining rule diagram. Drive the inference rule by considering the…

A: ANSWER: Backward Chaining: Backward chaining is otherwise called a backward derivation or backward…

Q: Design a set of states, rewards, and rules for an intelligent agent playing a simple board game. You…

A: Reinforcement Learning (RL):Reinforcement Learning (RL) is a type of machine learning paradigm where…

Q: Using the following predicates, any needed logical operators, and quantifiers if needed, translate…

A: According to the information given;- We have to follow the instruction in order to create…

Q: 1. Determine whether (p2g)^(¬P) =q.

A: Note: Answering the first question as per the guidelines. In order to show the equivalence of two…

Q: For the goal-based agent architecture given in the picture, write the pseudocode for the agent,…

A: Agents with goals expand on model-based agents. These agents can execute all the activities that…

Q: Q.2:- Consider the following example Training data: I am Sam Sam I am Sam I like Sam I do…

A: Probabilities of Bigram : P(Sam| <s> ) = 35P( I | SAM ) = 35P(Sam | am) = 12P(am | I )…

Concept explainers

Intelligent Machines

Machines that use artificial intelligence to learn from the environment and past experiences to perform better in the presence of variability and uncertainty are called intelligent machines. Intelligence develops according to environment and experience. It is human-like behavior. When the computer system or any programmed machine learns from the inputs and corresponding outputs, it can be called an intelligent machine.

Question

Example Let us consider a fuzzy system with two inputs x₁
and x2 (antecedents) and a single output y (consequent).
Inputs x and x₂ have three linguistic variables small, medium
and big with a triangular membership function. Output y has
two linguistic variables small and big with a triangular
membership function as shown in Figure below. The rule
base consists of the following two rules:
Rule 1: IF x is small AND xz is medium THEN y is big
Rule 2: IF xis medium AND x2 is big THEN y is small
Demonstrate entire process of fuzzification, aggregation and
defuzzification in a fuzzy system and find the output when
the inputs X₁ and x₂ equal 3.89 and 5.58, respectively.
X1
(a)
x₁= 3.89
small
Amedium
9
1
min[μ (x₁), M (x₂)]
AND
AND
big
X2
Amedium Rule 1
mini
ARU
9
Rule 2
min
X2=5.58
Aggregation of Mig (y) and small
big
small
(b)
y
(c)
small
big

Expert Solution

This question has been solved!

Explore an expertly crafted, step-by-step solution for a thorough understanding of key concepts.

SEE SOLUTION Check out a sample Q&A here

Step 1

VIEW

Step 2

VIEW

Step by step

Solved in 2 steps

SEE SOLUTION Check out a sample Q&A here

Knowledge Booster

Learn more about

Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, computer-science and related others by exploring similar questions and additional content below.

Similar questions

Problem 10. A decision tree is a representation of a complex decision process with multiple steps and factors. Consider the following decision tree representing the process of buying a car: Colour = Red No. Yes Model > 2010 Colour = Yellow No No Yes Yes Mileage < 50000KM Make = Ferrari Buy Dont Buy Yes No No Yes Buy Don't Buy Buy Dont Buy For this diagram: a) Write an argument, using propositions and logic connectives, based on the diagram. Determine whether we should buy a red Ford from 2008 with 34000KM mileage. b) Write at least one argument, using propositions and logic connectives, leading to the outcome that a red Ford was purchased.
A group of international experts in fuzzy set theory were invited to classify the overall performance of two research scholars, after a lot of discussion they agreed to consider the following attributes(Creativity, presentation skills) in the classification of the scholar design a fuzzy inference system to find how would they judge similarity of the research scholars with varying attributes ?Explain the procedure in details. Solve using theoretical fuzzy logic rules, not code Skills 1 2 3 4 5 Creativity Presentation skills 1 No creativity Bad 2 Fair Fair 3 Good Good 4 Very good Very good 5 Excellent Excellent Creativity 1 5 4 3 2 1 2 4 4 3 2 1 345. 4 3 3 2 1 + 3 2 2 I 1 32111
A group of international experts in fuzzy set theory were invited to classify the overall performance of two research scholars, after a lot of discussion they agreed to consider the following attributes(Creativity, presentation skills) in the classification of the scholar .design a fuzzy inference system to find how would they judge similarity of the research scholars with varying attributes ?Explain the procedure in details. Creativity Skills 1 2 3 4 5 Presentation skills 1 No creativity Bad 2 Fair Fair 3 Good Good 4 Very good 5 Excellent Very good Excellent Creativity 1 5 4 3 2 1 2 4 4 3 2 1 3 4 3 3 2 1 + 3 2 2 1 1 5 3 2 1 1 1 B- Draw the Genetic algorithm flowchart and write the code for each step.
You build a model predicting blood pressure as a function of three variables: weight (numeric) age (numeric) income (categorical: low, medium, high) You first specify your model as: blood pressure ~ age * income + weight How many parameters (k) does your model have? (Remember, we do not count the grand mean in k) You change the above model specification to be: blood pressure ~ age * income + weight * income How many parameters does your model have now? You change your model to include the three-way interaction (which, remember, includes all two-way interactions and main effects, too!) Your model now looks like this: blood pressure ~ age * income * weight How many parameters does your model have now?
Write a Java program to simulate the behaviour of a model-based agent for a vacuum cleaner environment based on the following conditions: The vacuum cleaner can move to one of 4 squares: A, B, C, or D as shown in Table 1. Table 1: vacuum cleaner environment A B C D The vacuum cleaner checks the status of all squares and takes action based on the following order: If all squares are clean, the vacuum cleaner stays in its current location. If the current location is not clean, the vacuum cleaner stays in its current location to clean it up. The vacuum cleaner can only move horizontally or vertically (cannot move diagonally). The vacuum cleaner moves only one square at a time. Horizontal moves have the highest priority over vertical moves. The vacuum cleaner moves to another square only when it needs to be cleaned up. If a diagonal square needs to be cleaned up, the vacuum cleaner moves to its neighbour vertical square first. The vacuum cleaner action is…
H1. Compute the value of an European Call option at time 0 for the following parameters: strike, K = 120, maturity 1 year, σ = 0.15, S0 = 120 and interest rate, r = 0.02: (a) by implementing, using Python, R, C++ or Matlab, a binomial model where n = 100, 1000, or 10000. For each value of n compute the error (difference between option value obtained using the B-S model and the one from the binomial model). Compute ∆0.
c) Consider the following knowledge base consisting of rules and facts, F& S THEN: E E THEN: T F& R THEN: M Facts R M THEN: T N THEN: C T& DTHEN: I C THEN: T ETHEN: D F Using backward chaining, determine if I is a fact or note ii) Given that the facts are altered to S and F determine using forward chaining if I is a fact or not.
Consider the training dataset given in Table P3.5. a. Construct a decision tree from the given data using "information gain" based splitting. Table P3.5 D1 D2 D3 D4 D5 D6 D7 D8 D9 Day D10 D11 D12 D13 D14 sunny sunny overcast rain rain Outlook rain overcast sunny sunny rain sunny overcast overcast rain hot hot hot mild cool cool cool mild cool mild mild mild hot mild Temperature high high high high normal normal Humidity normal high normal normal normal high normal high (Outlook sunny, Temperature cool, Humidity high, Wind - strong) ▪ weak Wind strong weak weak weak strong strong weak weak weak strong strong weak strong no no yes yes yes no yes no yes yes yes yes yes no PlayTennis
Consider a proof system P in the style of box-proof which only have one logical connective A. The system only has one rule given by: [X] Y YAX Here, X and Y can represent any formula. Tick each that applies. In the proof system P it is possible to derive the formula ((AAC)AB)AA In the proof system P it is possible to derive AA(AA A) In the proof system P it is possible to derive the formula AAA In the proof system P it is possible to derive (AAA)^ A In the proof system P it is not possible to derive (AA B)A(BAA)