Fuzzy Logic BY: ASHLEY REYNOLDS. Where Fuzzy Logic Falls in the Field of Mathematics  Mathematics  Mathematical Logic and Foundations  Fuzzy Logic.

Slides:



Advertisements
Similar presentations
Fuzzy Logic 11/6/2001. Agenda General Definition Applications Formal Definitions Operations Rules Fuzzy Air Conditioner Controller Structure.
Advertisements

Sahar Mosleh PageCalifornia State University San Marcos 1 Introductory Concepts This section of the course introduces the concept of digital circuits and.
Lecture 4 Fuzzy expert systems: Fuzzy logic
Fuzzy Logic and its Application to Web Caching
Soft Computing. Per Printz Madsen Section of Automation and Control
CLASSICAL LOGIC and FUZZY LOGIC. CLASSICAL LOGIC In classical logic, a simple proposition P is a linguistic, or declarative, statement contained within.
AI TECHNIQUES Fuzzy Logic (Fuzzy System). Fuzzy Logic : An Idea.
Fuzzy Expert Systems. Lecture Outline What is fuzzy thinking? What is fuzzy thinking? Fuzzy sets Fuzzy sets Linguistic variables and hedges Linguistic.
FUZZY SYSTEMS. Fuzzy Systems Fuzzy Sets – To quantify and reason about fuzzy or vague terms of natural language – Example: hot, cold temperature small,
Fuzzy Sets and Fuzzification Michael J. Watts
Fuzzy Logic Frank Costanzo – MAT 7670 Spring 2012.
GATE Reactive Behavior Modeling Fuzzy Logic (GATE-561) Dr.Çağatay ÜNDEĞER Instructor Middle East Technical University, GameTechnologies Bilkent University,
Fuzzy Expert System.
Fuzzy Medical Image Segmentation
Chapter 18 Fuzzy Reasoning.
1 Chapter 18 Fuzzy Reasoning. 2 Chapter 18 Contents (1) l Bivalent and Multivalent Logics l Linguistic Variables l Fuzzy Sets l Membership Functions l.
WELCOME TO THE WORLD OF FUZZY SYSTEMS. DEFINITION Fuzzy logic is a superset of conventional (Boolean) logic that has been extended to handle the concept.
Fuzzy Logic Dave Saad CS498. Origin Proposed as a mathematical model similar to traditional set theory but with the possibility of partial set membership.
Introduction What is Fuzzy Logic? HOW DOES FL WORK? Differences between Classical set (crisps) and Fuzzy set theory Example 1 Example 2 Classifying Houses.
Introduction to Fuzzy Logic Control
Fuzzy Systems and Applications
Boolean Logic & Truth Tables In today’s lesson we will look at: a reminder about truth values and NOT, AND, OR and EOR truth tables operator precedence.
Fuzzy Logic Mark Strohmaier CSE 335/435.
Fuzzy Logic. Priyaranga Koswatta Mundhenk and Itti, 2007.
FUZZY LOGIC Babu Appat. OVERVIEW What is Fuzzy Logic? Where did it begin? Fuzzy Logic vs. Neural Networks Fuzzy Logic in Control Systems Fuzzy Logic in.
9/3/2015Intelligent Systems and Soft Computing1 Lecture 4 Fuzzy expert systems: Fuzzy logic Introduction, or what is fuzzy thinking? Introduction, or what.
Fuzzy Logic Conception Introduced by Lotfi Zadeh in 1960s at Berkley Wanted to expand crisp logic.
Introduction to Innovative Design Thinking
Fuzzy Sets Introduction/Overview Material for these slides obtained from: Modern Information Retrieval by Ricardo Baeza-Yates and Berthier Ribeiro-Neto.
Fuzzy Logic. Lecture Outline Fuzzy Systems Fuzzy Sets Membership Functions Fuzzy Operators Fuzzy Set Characteristics Fuzziness and Probability.
CCSB354 ARTIFICIAL INTELLIGENCE
Fuzzy Logic. WHAT IS FUZZY LOGIC? Definition of fuzzy Fuzzy – “not clear, distinct, or precise; blurred” Definition of fuzzy logic A form of knowledge.
 Definition Definition  Bit of History Bit of History  Why Fuzzy Logic? Why Fuzzy Logic?  Applications Applications  Fuzzy Logic Operators Fuzzy.
Computer Science: A Structured Programming Approach Using C1 Objectives ❏ To understand how decisions are made in a computer ❏ To understand the logical.
Logical Systems and Knowledge Representation Fuzzy Logical Systems 1.
Fuzzy Sets and Control. Fuzzy Logic The definition of Fuzzy logic is a form of multi-valued logic derived frommulti-valued logic fuzzy setfuzzy set theory.
Chapter 2 Sets and Functions Section 2.1 Sets. A set is a particular type of mathematical idea that is used to categorize or group different collections.
Artificial Intelligence CIS 342 The College of Saint Rose David Goldschmidt, Ph.D.
Basic Concepts of Fuzzy Logic Apparatus of fuzzy logic is built on: Fuzzy sets: describe the value of variables Linguistic variables: qualitatively and.
AI Fuzzy Systems. History, State of the Art, and Future Development Sde Seminal Paper “Fuzzy Logic” by Prof. Lotfi Zadeh, Faculty in Electrical.
Fuzzy Expert System n Introduction n Fuzzy sets n Linguistic variables and hedges n Operations of fuzzy sets n Fuzzy rules n Summary.
Fuzzy Sets and Logic Sarah Spence Adams Discrete Mathematics.
Fuzzy Logic Artificial Intelligence Chapter 9. Outline Crisp Logic Fuzzy Logic Fuzzy Logic Applications Conclusion “traditional logic”: {true,false}
Aisha Iqbal (CT-084) Kanwal Hakeem (CT-098) Tehreem Mushtaq (CT-078) Talha Syed (CT-111)
Introduction to programming in java Lecture 11 Boolean Expressions and Assignment no. 2.
Computer Science: A Structured Programming Approach Using C1 Objectives ❏ To understand how decisions are made in a computer ❏ To understand the logical.
Fuzzy Logic 1. Introduction Form of multivalued logic Deals reasoning that is approximate rather than precise The fuzzy logic variables may have a membership.
Dinner for Two. Fuzzify Inputs Apply Fuzzy Operator.
S PEED CONTROL OF DC MOTOR BY FUZZY CONTROLLER MD MUSTAFA KAMAL ROLL NO M E (CONTROL AND INSTRUMENTATION)
Chapter 3: Fuzzy Rules & Fuzzy Reasoning Extension Principle & Fuzzy Relations (3.2) Fuzzy if-then Rules(3.3) Fuzzy Reasonning (3.4)
CPS120 Introduction to Computer Science
CHAPTER 5 Handling Uncertainty BIC 3337 EXPERT SYSTEM.
Introduction to Fuzzy Logic and Fuzzy Systems
Fuzzy Inference System
Artificial Intelligence CIS 342
Selection—Making Decisions
Meaning of “fuzzy” Covered with fuzz; Of or resembling fuzz;
Fuzzy Logic 11/6/2001.
Introduction To Robot Sensors
Meaning of “fuzzy”, Definition of Fuzzy Logic
Fuzzy Logic and Fuzzy Sets
Fuzzy Control Tutorial
Introduction To Robot Decision Making
CLASSICAL LOGIC and FUZZY LOGIC
Meaning of “fuzzy”, Definition of Fuzzy Logic
Topics discussed in this section:
Selection—Making Decisions
Topics discussed in this section:
Meaning of “fuzzy”, Definition of Fuzzy Logic
Presentation transcript:

Fuzzy Logic BY: ASHLEY REYNOLDS

Where Fuzzy Logic Falls in the Field of Mathematics  Mathematics  Mathematical Logic and Foundations  Fuzzy Logic  Computer Science  Logic in Artificial Intelligence  Reasoning Under Uncertainty  Information and Communication, Circuits  Fuzzy Sets and Logic

Boolean Logic  The logic that we have learned about so far falls in the classification of Boolean logic. In Boolean logic all values are reduced to either “True” or “False”  An example of this can be seen by looking back to Discrete.  Truth Tables

Fuzzy Logic  The term Fuzzy Logic was introduced in 1965 by Lotfi Zadeh who was working on the problem of a computer understanding natural language.  Natural language is not easily translated into completely true or completely false.  Fuzzy Logic is a form of many-valued logic; it deals with reasoning that is approximate rather than fixed and exact.  Fuzzy logic has been extended to handle the concept of partial truth, where the truth value may range between completely true and completely false

Example  “Fuzzy logic includes 0 and 1 as extreme cases of truth (or "the state of matters" or "fact") but also includes the various states of truth in between so that, for example, the result of a comparison between two things could be not "tall" or "short" but ".38 of tallness”(Rouse)  Another example is asking people to identify a color. You will receive answers of varying degree.

What’s the Problem  The main “problem” that is trying to be solved is in the application of fuzzy logic to the real world.  Fuzzy logic has been used in many areas of the real world to improve the everyday life of a population  The first notable application was on the high-speed train in Sendai, in which fuzzy logic was able to improve the economy, comfort, and precision of the ride. It has also been used in recognition of hand written symbols in Sony pocket computers.

Example of an application  A temperature measurement for anti-lock breaks might have several separate membership functions defining particular temperature ranges needed to control the brakes properly.  Each function maps the same temperature value to a truth value in the 0 to 1 range.  These truth values can then be used to determine how the brakes should be controlled.

Example Continued  The meanings of the expressions cold, warm, and hot are represented by functions mapping a temperature scale.  A point on that scale has three "truth values"—one for each of the three functions. The vertical line in the image represents a particular temperature that the three arrows (truth values) gauge. Since the red arrow points to zero, this temperature may be interpreted as "not hot". The orange arrow (pointing at 0.2) may describe it as "slightly warm" and the blue arrow (pointing at 0.8) "fairly cold".

Extra  Fuzzy logic usually uses IF-THEN rules, or constructs.  Rules are usually expressed in the form: IF variable IS property THEN action  There is no "ELSE" – all of the rules are evaluated, because the value might be “true" and “false" at the same time to different degrees.  The AND, OR, and NOT operators of Boolean logic exist in fuzzy logic, usually defined as the minimum, maximum, and complement; when they are defined this way, they are called the Zadeh operators.

Example IF temperature IS very cold THEN stop fan IF temperature IS cold THEN turn down fan IF temperature IS normal THEN maintain level IF temperature IS hot THEN speed up fan For example, a simple temperature regulator that uses a fan might look like this:

Review  Fuzzy Logic is a type of logic that recognizes more than simple true and false values.  Prepositions can be represented with degrees of truthfulness and falsehood.  This is a lot more representative of how our brains work.

Resources  Rouse, Margaret. “Fuzzy Logic”. Whatis.com. July Web. 25 September,  “Fuzzy Logic Introduction”. Fuzzy Logic and Its Uses. Web. 25 September,  Kaehler, Stephen. “Fuzzy Logic – An Introduction” seattlerobotics.org. June Web. 25 September ON ON HQQFjAJ&url=http%3A%2F%2Fpayam.malakut.org%2Farchives%2FFuzzy_logic.doc &ei=1XhJUrzcJenk4AO4j4HoDw&usg=AFQjCNEm24XDh03KHs2LDqli68x- Xv0Ckg&sig2=4vsuxq1dypbtG8wgRowCqA