SlideShare une entreprise Scribd logo
1  sur  56
 
Knowledge & Inexact Reasoning ,[object Object],[object Object],[object Object],[object Object],[object Object]
Inexact Reasoning ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Forms of Inexact Knowledge ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Inexact Knowledge - Example ,[object Object],default -   A wants to take a bus belief, (un)certainty  - it's the neighbor B probability, default, uncertainty -   the neighbor goes home by car  default -   A wants to get a lift  default -   A wants to go home  Q:  Which forms of inexact knowledge and reasoning are involved here?
Examples of Inexact Knowledge ,[object Object],Fuzzy   -  a few hundred yards define a mapping from " #hundreds " to ' few ', ' many ', ... not uncertain or incomplete but graded, vague Probabilistic   -  the neighbor usually goes by car probability based on measure of how often he takes car;  calculates  always   p(F) = 1 - p( ¬F) Belief   -  it's his next-door neighbor B   "reasoned assumption", assumed to be true Default   -  A wants to take a bus   assumption based on commonsense knowledge
Dealing with Inexact Knowledge ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Uncertainty and Rules ,[object Object],[object Object],[object Object],[object Object],[object Object]
Figure 5.1 Major Uncertainties in Rule-Based Expert Systems
Figure 5.2 Uncertainties in Individual Rules
Figure 5.3 Uncertainty Associated with the Compatibilities of Rules
Figure 5.4 Uncertainty Associated with Conflict Resolution
Goal of Knowledge Engineer ,[object Object],[object Object],[object Object]
Verification vs. Validation ,[object Object],[object Object],[object Object],[object Object]
Ad Hoc Methods ,[object Object],[object Object],[object Object]
Sources of Uncertainty ,[object Object],[object Object]
Uncertainty in Conflict Resolution ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Uncertainty ,[object Object],[object Object],[object Object]
Uncertainty ,[object Object],[object Object],[object Object]
Certainty Factors ,[object Object]
Difficulties with Bayesian Method ,[object Object],[object Object],[object Object]
Belief and Disbelief ,[object Object],[object Object],[object Object],[object Object]
Belief and Disbelief ,[object Object],[object Object],[object Object]
Likelihood of Belief / Disbelief ,[object Object],[object Object],[object Object]
Measures of Belief and Disbelief ,[object Object],[object Object],[object Object],[object Object]
Certainty Factor Values ,[object Object],[object Object],[object Object],[object Object]
Threshold Values ,[object Object],[object Object],[object Object],[object Object]
Difficulties with Certainty Factors ,[object Object],[object Object],[object Object]
Dempster-Shafer Theory ,[object Object],[object Object]
Dempster-Shafer ,[object Object],[object Object]
Dempster-Shafer ,[object Object],[object Object],[object Object],[object Object]
Dempster-Shafer ,[object Object],[object Object],[object Object],[object Object]
Dempster-Shafer ,[object Object],[object Object],[object Object],[object Object],[object Object]
Dempster-Shafer ,[object Object],[object Object],[object Object],[object Object],[object Object]
Dempster-Shafer ,[object Object],[object Object]
Dempster-Shafer ,[object Object],[object Object],[object Object]
Dempster-Shafer ,[object Object],[object Object],[object Object],[object Object]
Dempster-Shafer ,[object Object],[object Object],[object Object]
Dempster-Shafer ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Approximate Reasoning ,[object Object],[object Object],[object Object]
Fuzzy Sets and Natural Language ,[object Object],[object Object],[object Object],[object Object],[object Object]
Fuzzy Sets and Natural Language  ,[object Object],[object Object],[object Object],[object Object],[object Object]
Fuzzy Set Operations ,[object Object],[object Object]
Fuzzy Set Operations  Set equality Set Complement Set Containment Proper Subset Set Union Set Intersection Set Product Power of a Set Probabilistic Sum Bounded Sum Bounded Product Bounded Difference Concentration Dilation Intensification Normalization
Fuzzy Relations ,[object Object],[object Object],[object Object],[object Object]
Fuzzy Relations ,[object Object],[object Object],[object Object]
Table 5.7 Some Applications of Fuzzy Theory
Table 5.8 Some Fuzzy Terms of Natural Language
Linguistic Variables ,[object Object],[object Object],[object Object]
Extension Principle ,[object Object],[object Object],[object Object]
Fuzzy Logic ,[object Object],[object Object]
Possibility and Probability and Fuzzy Logic ,[object Object],[object Object]
Translation Rules ,[object Object],[object Object],[object Object],[object Object],[object Object]
State of Uncertainty Commercial Applications ,[object Object],[object Object],[object Object],[object Object],[object Object]
Summary ,[object Object],[object Object],[object Object],[object Object]
Summary ,[object Object],[object Object]

Contenu connexe

Tendances

Spatial data analysis
Spatial data analysisSpatial data analysis
Spatial data analysisJohan Blomme
 
REMOTE SENSING
REMOTE SENSINGREMOTE SENSING
REMOTE SENSINGKANNAN
 
Remote sensing application in agriculture & forestry_Dr Menon A R R (The Kera...
Remote sensing application in agriculture & forestry_Dr Menon A R R (The Kera...Remote sensing application in agriculture & forestry_Dr Menon A R R (The Kera...
Remote sensing application in agriculture & forestry_Dr Menon A R R (The Kera...India Water Portal
 
Image enhancement technique digital image analysis, in remote sensing ,P K MANI
Image enhancement technique  digital image analysis, in remote sensing ,P K MANIImage enhancement technique  digital image analysis, in remote sensing ,P K MANI
Image enhancement technique digital image analysis, in remote sensing ,P K MANIP.K. Mani
 
LiDAR Data Processing and Classification
LiDAR Data Processing and ClassificationLiDAR Data Processing and Classification
LiDAR Data Processing and ClassificationMichal Bularz
 
Sentinel 2
Sentinel 2Sentinel 2
Sentinel 2Openmaps
 
Fundamentals of Remote Sensing
Fundamentals of Remote Sensing Fundamentals of Remote Sensing
Fundamentals of Remote Sensing Pallab Jana
 
Introduction to Maximum Likelihood Estimator
Introduction to Maximum Likelihood EstimatorIntroduction to Maximum Likelihood Estimator
Introduction to Maximum Likelihood EstimatorAmir Al-Ansary
 
Maximum Likelihood Estimation
Maximum Likelihood EstimationMaximum Likelihood Estimation
Maximum Likelihood Estimationguestfee8698
 
3.7 outlier analysis
3.7 outlier analysis3.7 outlier analysis
3.7 outlier analysisKrish_ver2
 
Commonly used ground truth equipments
Commonly used ground truth equipmentsCommonly used ground truth equipments
Commonly used ground truth equipmentsHimangshuKalita10
 
Lidar : light detection and rangeing
Lidar : light detection and rangeingLidar : light detection and rangeing
Lidar : light detection and rangeingRahul Bhagore
 
Remote sensing
Remote sensingRemote sensing
Remote sensingKU Leuven
 

Tendances (20)

IRNSS (NAVIC)
IRNSS (NAVIC)IRNSS (NAVIC)
IRNSS (NAVIC)
 
Spatial data analysis
Spatial data analysisSpatial data analysis
Spatial data analysis
 
REMOTE SENSING
REMOTE SENSINGREMOTE SENSING
REMOTE SENSING
 
Manual of Remote Sensing
Manual of Remote SensingManual of Remote Sensing
Manual of Remote Sensing
 
Data cleaning-outlier-detection
Data cleaning-outlier-detectionData cleaning-outlier-detection
Data cleaning-outlier-detection
 
Remote sensing application in agriculture & forestry_Dr Menon A R R (The Kera...
Remote sensing application in agriculture & forestry_Dr Menon A R R (The Kera...Remote sensing application in agriculture & forestry_Dr Menon A R R (The Kera...
Remote sensing application in agriculture & forestry_Dr Menon A R R (The Kera...
 
Image enhancement technique digital image analysis, in remote sensing ,P K MANI
Image enhancement technique  digital image analysis, in remote sensing ,P K MANIImage enhancement technique  digital image analysis, in remote sensing ,P K MANI
Image enhancement technique digital image analysis, in remote sensing ,P K MANI
 
LiDAR Data Processing and Classification
LiDAR Data Processing and ClassificationLiDAR Data Processing and Classification
LiDAR Data Processing and Classification
 
Sentinel 2
Sentinel 2Sentinel 2
Sentinel 2
 
Digital image processing
Digital image processingDigital image processing
Digital image processing
 
Fundamentals of Remote Sensing
Fundamentals of Remote Sensing Fundamentals of Remote Sensing
Fundamentals of Remote Sensing
 
Introduction to Maximum Likelihood Estimator
Introduction to Maximum Likelihood EstimatorIntroduction to Maximum Likelihood Estimator
Introduction to Maximum Likelihood Estimator
 
Maximum Likelihood Estimation
Maximum Likelihood EstimationMaximum Likelihood Estimation
Maximum Likelihood Estimation
 
Uncertainty in AI
Uncertainty in AIUncertainty in AI
Uncertainty in AI
 
Introduction to soft computing
 Introduction to soft computing Introduction to soft computing
Introduction to soft computing
 
Optical remote sensing
Optical remote sensingOptical remote sensing
Optical remote sensing
 
3.7 outlier analysis
3.7 outlier analysis3.7 outlier analysis
3.7 outlier analysis
 
Commonly used ground truth equipments
Commonly used ground truth equipmentsCommonly used ground truth equipments
Commonly used ground truth equipments
 
Lidar : light detection and rangeing
Lidar : light detection and rangeingLidar : light detection and rangeing
Lidar : light detection and rangeing
 
Remote sensing
Remote sensingRemote sensing
Remote sensing
 

En vedette

Bayeasian inference
Bayeasian inferenceBayeasian inference
Bayeasian inferenceGlobal Polis
 
ConvNetJS & CaffeJS
ConvNetJS & CaffeJSConvNetJS & CaffeJS
ConvNetJS & CaffeJSAnyline
 
Applied Bayesian Inference with PyMC
Applied Bayesian Inference with PyMCApplied Bayesian Inference with PyMC
Applied Bayesian Inference with PyMCMarco Santoni
 
Bayesian Inference using b8
Bayesian Inference using b8Bayesian Inference using b8
Bayesian Inference using b8Dave Ross
 
Text Detection Strategies
Text Detection StrategiesText Detection Strategies
Text Detection StrategiesAnyline
 
Multisensor Data Fusion : Techno Briefing
Multisensor Data Fusion : Techno BriefingMultisensor Data Fusion : Techno Briefing
Multisensor Data Fusion : Techno BriefingPaveen Juntama
 
Ed Batista, Interpersonal Dynamics (aka Touchy Feely) @StanfordBiz, Class 4: ...
Ed Batista, Interpersonal Dynamics (aka Touchy Feely) @StanfordBiz, Class 4: ...Ed Batista, Interpersonal Dynamics (aka Touchy Feely) @StanfordBiz, Class 4: ...
Ed Batista, Interpersonal Dynamics (aka Touchy Feely) @StanfordBiz, Class 4: ...Ed Batista
 
Introduction to CLIPS Expert System
Introduction to CLIPS Expert SystemIntroduction to CLIPS Expert System
Introduction to CLIPS Expert SystemMotaz Saad
 
Deep Learning in iOS Tutorial
Deep Learning in iOS TutorialDeep Learning in iOS Tutorial
Deep Learning in iOS TutorialAnyline
 
Bayesian Belief Networks for dummies
Bayesian Belief Networks for dummiesBayesian Belief Networks for dummies
Bayesian Belief Networks for dummiesGilad Barkan
 
FORWARD CHAINING AND BACKWARD CHAINING SYSTEMS IN ARTIFICIAL INTELIGENCE
FORWARD CHAINING AND BACKWARD CHAINING SYSTEMS IN ARTIFICIAL INTELIGENCEFORWARD CHAINING AND BACKWARD CHAINING SYSTEMS IN ARTIFICIAL INTELIGENCE
FORWARD CHAINING AND BACKWARD CHAINING SYSTEMS IN ARTIFICIAL INTELIGENCEJohnLeonard Onwuzuruigbo
 

En vedette (15)

Certainty Factor Theory
Certainty Factor TheoryCertainty Factor Theory
Certainty Factor Theory
 
Bayeasian inference
Bayeasian inferenceBayeasian inference
Bayeasian inference
 
ConvNetJS & CaffeJS
ConvNetJS & CaffeJSConvNetJS & CaffeJS
ConvNetJS & CaffeJS
 
Applied Bayesian Inference with PyMC
Applied Bayesian Inference with PyMCApplied Bayesian Inference with PyMC
Applied Bayesian Inference with PyMC
 
Multiple Classifier Systems
Multiple Classifier SystemsMultiple Classifier Systems
Multiple Classifier Systems
 
Bayesian Inference using b8
Bayesian Inference using b8Bayesian Inference using b8
Bayesian Inference using b8
 
Text Detection Strategies
Text Detection StrategiesText Detection Strategies
Text Detection Strategies
 
Multisensor Data Fusion : Techno Briefing
Multisensor Data Fusion : Techno BriefingMultisensor Data Fusion : Techno Briefing
Multisensor Data Fusion : Techno Briefing
 
Ed Batista, Interpersonal Dynamics (aka Touchy Feely) @StanfordBiz, Class 4: ...
Ed Batista, Interpersonal Dynamics (aka Touchy Feely) @StanfordBiz, Class 4: ...Ed Batista, Interpersonal Dynamics (aka Touchy Feely) @StanfordBiz, Class 4: ...
Ed Batista, Interpersonal Dynamics (aka Touchy Feely) @StanfordBiz, Class 4: ...
 
Ai 7
Ai 7Ai 7
Ai 7
 
Introduction to CLIPS Expert System
Introduction to CLIPS Expert SystemIntroduction to CLIPS Expert System
Introduction to CLIPS Expert System
 
Mycin
MycinMycin
Mycin
 
Deep Learning in iOS Tutorial
Deep Learning in iOS TutorialDeep Learning in iOS Tutorial
Deep Learning in iOS Tutorial
 
Bayesian Belief Networks for dummies
Bayesian Belief Networks for dummiesBayesian Belief Networks for dummies
Bayesian Belief Networks for dummies
 
FORWARD CHAINING AND BACKWARD CHAINING SYSTEMS IN ARTIFICIAL INTELIGENCE
FORWARD CHAINING AND BACKWARD CHAINING SYSTEMS IN ARTIFICIAL INTELIGENCEFORWARD CHAINING AND BACKWARD CHAINING SYSTEMS IN ARTIFICIAL INTELIGENCE
FORWARD CHAINING AND BACKWARD CHAINING SYSTEMS IN ARTIFICIAL INTELIGENCE
 

Similaire à Inexact reasoning

pydata_confernence_july_2016_modified_sunday_final
pydata_confernence_july_2016_modified_sunday_finalpydata_confernence_july_2016_modified_sunday_final
pydata_confernence_july_2016_modified_sunday_finalAustin Powell
 
Final mayo's aps_talk
Final mayo's aps_talkFinal mayo's aps_talk
Final mayo's aps_talkjemille6
 
Is it important to explain a theorem? A case study in UML and ALCQI
Is it important to explain a theorem? A case study in UML and ALCQIIs it important to explain a theorem? A case study in UML and ALCQI
Is it important to explain a theorem? A case study in UML and ALCQIAlexandre Rademaker
 
Is there any a novel best theory for uncertainty?
Is there any a novel best theory for uncertainty?  Is there any a novel best theory for uncertainty?
Is there any a novel best theory for uncertainty? Andino Maseleno
 
Net set logical reasoning - Critical Thinking
Net set logical reasoning - Critical Thinking  Net set logical reasoning - Critical Thinking
Net set logical reasoning - Critical Thinking amitkuls
 
The role of background assumptions in severity appraisal (
The role of background assumptions in severity appraisal (The role of background assumptions in severity appraisal (
The role of background assumptions in severity appraisal (jemille6
 
chap4_Parametric_Methods.ppt
chap4_Parametric_Methods.pptchap4_Parametric_Methods.ppt
chap4_Parametric_Methods.pptShayanChowdary
 
0hypothesis testing.pdf
0hypothesis testing.pdf0hypothesis testing.pdf
0hypothesis testing.pdfAyushPandey175
 
Statistical skepticism: How to use significance tests effectively
Statistical skepticism: How to use significance tests effectively Statistical skepticism: How to use significance tests effectively
Statistical skepticism: How to use significance tests effectively jemille6
 
Earthquake dhnjggbnkkkknvcxsefghjk gyjhvcdyj
Earthquake dhnjggbnkkkknvcxsefghjk gyjhvcdyjEarthquake dhnjggbnkkkknvcxsefghjk gyjhvcdyj
Earthquake dhnjggbnkkkknvcxsefghjk gyjhvcdyjjansisce
 

Similaire à Inexact reasoning (20)

pydata_confernence_july_2016_modified_sunday_final
pydata_confernence_july_2016_modified_sunday_finalpydata_confernence_july_2016_modified_sunday_final
pydata_confernence_july_2016_modified_sunday_final
 
Russo Ihpst Seminar
Russo Ihpst SeminarRusso Ihpst Seminar
Russo Ihpst Seminar
 
Russo Vub Seminar
Russo Vub SeminarRusso Vub Seminar
Russo Vub Seminar
 
Russo Vub Seminar
Russo Vub SeminarRusso Vub Seminar
Russo Vub Seminar
 
Final mayo's aps_talk
Final mayo's aps_talkFinal mayo's aps_talk
Final mayo's aps_talk
 
Is it important to explain a theorem? A case study in UML and ALCQI
Is it important to explain a theorem? A case study in UML and ALCQIIs it important to explain a theorem? A case study in UML and ALCQI
Is it important to explain a theorem? A case study in UML and ALCQI
 
Rm 3 Hypothesis
Rm   3   HypothesisRm   3   Hypothesis
Rm 3 Hypothesis
 
CS3491-Unit-2 Uncertainty.pptx
CS3491-Unit-2 Uncertainty.pptxCS3491-Unit-2 Uncertainty.pptx
CS3491-Unit-2 Uncertainty.pptx
 
Is there any a novel best theory for uncertainty?
Is there any a novel best theory for uncertainty?  Is there any a novel best theory for uncertainty?
Is there any a novel best theory for uncertainty?
 
Hypothesis testing
Hypothesis testingHypothesis testing
Hypothesis testing
 
Net set logical reasoning - Critical Thinking
Net set logical reasoning - Critical Thinking  Net set logical reasoning - Critical Thinking
Net set logical reasoning - Critical Thinking
 
The role of background assumptions in severity appraisal (
The role of background assumptions in severity appraisal (The role of background assumptions in severity appraisal (
The role of background assumptions in severity appraisal (
 
Introductory Statistics
Introductory StatisticsIntroductory Statistics
Introductory Statistics
 
chap4_Parametric_Methods.ppt
chap4_Parametric_Methods.pptchap4_Parametric_Methods.ppt
chap4_Parametric_Methods.ppt
 
0hypothesis testing.pdf
0hypothesis testing.pdf0hypothesis testing.pdf
0hypothesis testing.pdf
 
Statistical skepticism: How to use significance tests effectively
Statistical skepticism: How to use significance tests effectively Statistical skepticism: How to use significance tests effectively
Statistical skepticism: How to use significance tests effectively
 
Hypothesis
HypothesisHypothesis
Hypothesis
 
Hypothesis testing
Hypothesis testingHypothesis testing
Hypothesis testing
 
Statistics
StatisticsStatistics
Statistics
 
Earthquake dhnjggbnkkkknvcxsefghjk gyjhvcdyj
Earthquake dhnjggbnkkkknvcxsefghjk gyjhvcdyjEarthquake dhnjggbnkkkknvcxsefghjk gyjhvcdyj
Earthquake dhnjggbnkkkknvcxsefghjk gyjhvcdyj
 

Dernier

Sports & Fitness Value Added Course FY..
Sports & Fitness Value Added Course FY..Sports & Fitness Value Added Course FY..
Sports & Fitness Value Added Course FY..Disha Kariya
 
Russian Escort Service in Delhi 11k Hotel Foreigner Russian Call Girls in Delhi
Russian Escort Service in Delhi 11k Hotel Foreigner Russian Call Girls in DelhiRussian Escort Service in Delhi 11k Hotel Foreigner Russian Call Girls in Delhi
Russian Escort Service in Delhi 11k Hotel Foreigner Russian Call Girls in Delhikauryashika82
 
Paris 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activityParis 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activityGeoBlogs
 
1029-Danh muc Sach Giao Khoa khoi 6.pdf
1029-Danh muc Sach Giao Khoa khoi  6.pdf1029-Danh muc Sach Giao Khoa khoi  6.pdf
1029-Danh muc Sach Giao Khoa khoi 6.pdfQucHHunhnh
 
Q4-W6-Restating Informational Text Grade 3
Q4-W6-Restating Informational Text Grade 3Q4-W6-Restating Informational Text Grade 3
Q4-W6-Restating Informational Text Grade 3JemimahLaneBuaron
 
Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...
Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...
Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...fonyou31
 
Introduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The BasicsIntroduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The BasicsTechSoup
 
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...Krashi Coaching
 
Beyond the EU: DORA and NIS 2 Directive's Global Impact
Beyond the EU: DORA and NIS 2 Directive's Global ImpactBeyond the EU: DORA and NIS 2 Directive's Global Impact
Beyond the EU: DORA and NIS 2 Directive's Global ImpactPECB
 
9548086042 for call girls in Indira Nagar with room service
9548086042  for call girls in Indira Nagar  with room service9548086042  for call girls in Indira Nagar  with room service
9548086042 for call girls in Indira Nagar with room servicediscovermytutordmt
 
Key note speaker Neum_Admir Softic_ENG.pdf
Key note speaker Neum_Admir Softic_ENG.pdfKey note speaker Neum_Admir Softic_ENG.pdf
Key note speaker Neum_Admir Softic_ENG.pdfAdmir Softic
 
APM Welcome, APM North West Network Conference, Synergies Across Sectors
APM Welcome, APM North West Network Conference, Synergies Across SectorsAPM Welcome, APM North West Network Conference, Synergies Across Sectors
APM Welcome, APM North West Network Conference, Synergies Across SectorsAssociation for Project Management
 
Activity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdfActivity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdfciinovamais
 
Measures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and ModeMeasures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and ModeThiyagu K
 
Disha NEET Physics Guide for classes 11 and 12.pdf
Disha NEET Physics Guide for classes 11 and 12.pdfDisha NEET Physics Guide for classes 11 and 12.pdf
Disha NEET Physics Guide for classes 11 and 12.pdfchloefrazer622
 
Accessible design: Minimum effort, maximum impact
Accessible design: Minimum effort, maximum impactAccessible design: Minimum effort, maximum impact
Accessible design: Minimum effort, maximum impactdawncurless
 

Dernier (20)

Sports & Fitness Value Added Course FY..
Sports & Fitness Value Added Course FY..Sports & Fitness Value Added Course FY..
Sports & Fitness Value Added Course FY..
 
Código Creativo y Arte de Software | Unidad 1
Código Creativo y Arte de Software | Unidad 1Código Creativo y Arte de Software | Unidad 1
Código Creativo y Arte de Software | Unidad 1
 
Russian Escort Service in Delhi 11k Hotel Foreigner Russian Call Girls in Delhi
Russian Escort Service in Delhi 11k Hotel Foreigner Russian Call Girls in DelhiRussian Escort Service in Delhi 11k Hotel Foreigner Russian Call Girls in Delhi
Russian Escort Service in Delhi 11k Hotel Foreigner Russian Call Girls in Delhi
 
Paris 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activityParis 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activity
 
1029-Danh muc Sach Giao Khoa khoi 6.pdf
1029-Danh muc Sach Giao Khoa khoi  6.pdf1029-Danh muc Sach Giao Khoa khoi  6.pdf
1029-Danh muc Sach Giao Khoa khoi 6.pdf
 
Q4-W6-Restating Informational Text Grade 3
Q4-W6-Restating Informational Text Grade 3Q4-W6-Restating Informational Text Grade 3
Q4-W6-Restating Informational Text Grade 3
 
INDIA QUIZ 2024 RLAC DELHI UNIVERSITY.pptx
INDIA QUIZ 2024 RLAC DELHI UNIVERSITY.pptxINDIA QUIZ 2024 RLAC DELHI UNIVERSITY.pptx
INDIA QUIZ 2024 RLAC DELHI UNIVERSITY.pptx
 
Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...
Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...
Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...
 
Introduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The BasicsIntroduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The Basics
 
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
 
Beyond the EU: DORA and NIS 2 Directive's Global Impact
Beyond the EU: DORA and NIS 2 Directive's Global ImpactBeyond the EU: DORA and NIS 2 Directive's Global Impact
Beyond the EU: DORA and NIS 2 Directive's Global Impact
 
9548086042 for call girls in Indira Nagar with room service
9548086042  for call girls in Indira Nagar  with room service9548086042  for call girls in Indira Nagar  with room service
9548086042 for call girls in Indira Nagar with room service
 
Key note speaker Neum_Admir Softic_ENG.pdf
Key note speaker Neum_Admir Softic_ENG.pdfKey note speaker Neum_Admir Softic_ENG.pdf
Key note speaker Neum_Admir Softic_ENG.pdf
 
APM Welcome, APM North West Network Conference, Synergies Across Sectors
APM Welcome, APM North West Network Conference, Synergies Across SectorsAPM Welcome, APM North West Network Conference, Synergies Across Sectors
APM Welcome, APM North West Network Conference, Synergies Across Sectors
 
Advance Mobile Application Development class 07
Advance Mobile Application Development class 07Advance Mobile Application Development class 07
Advance Mobile Application Development class 07
 
Mattingly "AI & Prompt Design: The Basics of Prompt Design"
Mattingly "AI & Prompt Design: The Basics of Prompt Design"Mattingly "AI & Prompt Design: The Basics of Prompt Design"
Mattingly "AI & Prompt Design: The Basics of Prompt Design"
 
Activity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdfActivity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdf
 
Measures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and ModeMeasures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and Mode
 
Disha NEET Physics Guide for classes 11 and 12.pdf
Disha NEET Physics Guide for classes 11 and 12.pdfDisha NEET Physics Guide for classes 11 and 12.pdf
Disha NEET Physics Guide for classes 11 and 12.pdf
 
Accessible design: Minimum effort, maximum impact
Accessible design: Minimum effort, maximum impactAccessible design: Minimum effort, maximum impact
Accessible design: Minimum effort, maximum impact
 

Inexact reasoning

  • 1.  
  • 2.
  • 3.
  • 4.
  • 5.
  • 6.
  • 7.
  • 8.
  • 9. Figure 5.1 Major Uncertainties in Rule-Based Expert Systems
  • 10. Figure 5.2 Uncertainties in Individual Rules
  • 11. Figure 5.3 Uncertainty Associated with the Compatibilities of Rules
  • 12. Figure 5.4 Uncertainty Associated with Conflict Resolution
  • 13.
  • 14.
  • 15.
  • 16.
  • 17.
  • 18.
  • 19.
  • 20.
  • 21.
  • 22.
  • 23.
  • 24.
  • 25.
  • 26.
  • 27.
  • 28.
  • 29.
  • 30.
  • 31.
  • 32.
  • 33.
  • 34.
  • 35.
  • 36.
  • 37.
  • 38.
  • 39.
  • 40.
  • 41.
  • 42.
  • 43.
  • 44. Fuzzy Set Operations Set equality Set Complement Set Containment Proper Subset Set Union Set Intersection Set Product Power of a Set Probabilistic Sum Bounded Sum Bounded Product Bounded Difference Concentration Dilation Intensification Normalization
  • 45.
  • 46.
  • 47. Table 5.7 Some Applications of Fuzzy Theory
  • 48. Table 5.8 Some Fuzzy Terms of Natural Language
  • 49.
  • 50.
  • 51.
  • 52.
  • 53.
  • 54.
  • 55.
  • 56.